Systems and methods for real-time tracking of a target tissue using imaging before and during therapy delivery

Information

  • Patent Grant
  • 10925579
  • Patent Number
    10,925,579
  • Date Filed
    Friday, October 30, 2015
    9 years ago
  • Date Issued
    Tuesday, February 23, 2021
    3 years ago
Abstract
Described herein are systems and methods for tracking a target tissue during therapy delivery. A system for identifying an anatomical structure and tracking the motion of the anatomical structure using imaging before and during delivery of a therapy to a patient includes an imaging module and a therapy module. In some cases, the imaging module is configured to identify a region of the anatomical structure in an image, and the therapy module is configured to deliver the therapy to a target tissue. A method for imaging during delivery of a therapy includes acquiring an image, identifying a region of an anatomical structure, tracking the region of the anatomical structure, integrating the tracking, generating a unique template library, determining if a pre-existing template matches the results or if the results should be updated as a new template, and delivering the therapy to the target tissue.
Description
INCORPORATION BY REFERENCE

All publications and patent applications mentioned in this specification are herein incorporated by reference in their entirety, as if each individual publication or patent application was specifically and individually indicated to be incorporated by reference in its entirety.


TECHNICAL FIELD

This invention relates generally to the imaging field, and more specifically to a new and useful system and method for real-time tracking of a target tissue using imaging before and during therapy delivery.


BACKGROUND

Therapeutic energy delivery from a distance involves transmission of energy waves to affect a target tissue inside a patient's body. Therapeutic delivery of ultrasound waves has been used in a wide variety of therapeutic interventions, including lithotripsy, drug delivery, cancer therapy, thrombolysis, and tissue ablation. Non-invasive delivery of focused energy may allow for more efficient delivery of energy to the target tissue, improved cost effectiveness of treatment, minimized trauma to the patient's body, and improved recovery time.


Delivering energy over a distance requires targeting accuracy and technological flexibility while minimizing invasiveness into the patient. However, current methods fail to adequately track the target tissue motion while concurrently delivering the energy or therapy. A tissue in the body moves relative to the energy-delivering source from either the unintended patient body motion or the internal organs' motion due to heartbeat, breathing, blood flow, or other physiological functions. Current methods stop delivering the energy or therapy when the tissue moves out of focus or visibility due, at least, to breathing or shadows and reinitiates energy or therapy delivery when the tissue reemerges. The stopping and starting of therapy or energy delivery can have unintended consequences for the patient, such as variable dosing, uneven or insufficient therapy delivery to the target tissue, and prolonged procedure times.


Conventional ultrasound systems for tracking a targeted soft tissue motion have a much lower signal-to-noise ratio. Further, the shape of a target image can change more as it moves within the image because of ultrasound beam scan orientation, tissue deformation, ultrasound signal distortion and other factors. Controlling these factors is desirable for effective and accurate therapeutic energy delivering to the target tissue. Since soft tissue deforms at a macroscopic level, conventional tracking systems cannot adequately track such tissue deformation and motion. Further, tracking and energy delivery will halt when a conventional system loses the target tissue, due to, for example, rib shadows or deep breaths that move the target out of sight. This happens regularly in conventional systems. Conventional systems are not configured to deal with these motions, and even more importantly they are not configured to properly recover tracking once the image reappears, requiring user input to relocate the lost target tissue in the image.


Thus, there is a need for a new and useful system and method for tracking a target tissue using imaging before and during therapy delivery. In particular, there is a need for new and useful systems and methods configured to accommodate when tissue moves out of focus or visibility, and even more importantly configured to automatically recover tracking when the image reappears. This invention provides such a new and useful system and method.


SUMMARY

A system for identifying at least one anatomical structure and tracking a motion of the at least one anatomical structure using imaging before and during delivery of a therapy to a patient, includes: an imaging module configured to identify a location and a feature of a region of the anatomical structure in an image, wherein the imaging module comprises a tracker, a detector, and an integrator; and a therapy module comprising an ultrasound treatment transducer configured to deliver the therapy to a target tissue in the patient.


Optionally, the imaging module is configured to, in real-time, track the anatomical structure using a feature identification technique.


Optionally, the imaging module is configured to use a histogram of the anatomical structure in the image, or a feature matching technique.


Optionally, the imaging module is configured to identify a location of the target tissue to be treated by the therapy module.


Optionally, the tracker is configured to identify a new location or a new feature of the region of the anatomical structure in response to a change in the location and the feature of the region of the anatomical structure.


Optionally, the detector is configured to identify a shape, a location, and a feature of the region of the anatomical structure.


Optionally, the tracker, detector, and integrator are implemented in graphics processor unit (GPU), field-programmable gate array (FPGA) or digital signal processor (DSP) or any other units containing computation capabilities.


Optionally, the therapy module is configured to function concurrently with the imaging module.


Optionally, the therapy module is configured to deliver therapy to the target tissue despite a change in the location or the feature of the region of the anatomical structure.


Optionally, the anatomical structure comprises the target tissue.


Optionally, at least one of breathing, blood flow, conscious movement, or unconscious movement of the patient changes the location and/or the feature of the region of the anatomical structure.


Optionally, the imaging module is configured to identify the location and the feature of the region of the anatomical structure in less than 1 second.


Optionally, the imaging module is configured to identify the location and the feature of the region of the anatomical structure in less than 5 milliseconds.


Optionally, the target tissue comprises a renal artery.


Optionally, the ultrasound treatment transducer is configured to provide renal denervation.


Optionally, the imaging module is configured to track the region of the anatomical structure is using a B-mode image, Harmonic Imaging, or 3D ultrasound imaging.


Optionally, the imaging module is configured to track the region of the anatomical structure using a color Doppler image, a color power Doppler image, or a directional color power Doppler mode image.


Optionally, the system further includes a filter, wherein the filter is configured to reduce noise in the image, such that the imaging module can determine the location and the feature of the region of the anatomical structure in the image.


Optionally, the filter is configured to provide a filtered image that is visible to the tracker, the detector, or both the tracker and detector.


Optionally, the system further includes a user interface for allowing a user to choose between viewing the filtered image or an unfiltered image.


Optionally, the location is an x and y coordinate.


Optionally, the location is an x, y, and z coordinate.


Optionally, the image is an ultrasound image.


Optionally, the integrator is configured to integrate results from the tracker and detector and direct the therapy module to deliver the therapy to the target tissue.


Optionally, the location is in a plane.


Optionally, the location is in a three-dimensional space.


Optionally, a plane of movement of the anatomical structure is substantially parallel to an imaging plane of the imaging module.


Optionally, the feature includes one or more of a characteristic, intensity, density, contrast, and shape of the region of the anatomical structure.


Optionally, the imaging module and the therapy module are configured to function consecutively using an interleaving mechanism.


Optionally, the imaging module and the therapy module are configured to function concurrently using a continuous mechanism.


Optionally, the therapy module is configured to predict a future location or a future feature of the target tissue and to deliver the therapy to the target tissue when the target tissue reaches the future location or the future feature.


Optionally, the therapy module is configured to provide lithotripsy.


Optionally, the lithotripsy comprises treatment of a kidney stone, gallstone, bile duct stone, or ureter stone.


Optionally, the tracker comprises a short-term detector.


Optionally, the detector comprises a long-term detector.


A system for tracking a renal artery during delivery of an ultrasound therapy to a patient, includes: an imaging module configured to identify a location and a feature of a region of an anatomical structure in an ultrasound image, wherein the imaging module comprises a tracker, a detector, and an integrator; and a therapy module comprising an ultrasound treatment transducer configured to deliver the ultrasound therapy to the renal artery, wherein the ultrasound treatment transducer is configured to be mechanically moved and/or electronically controlled.


Optionally, the ultrasound treatment transducer is configured to be moved by a motion control mechanism to move the ultrasound treatment transducer.


Optionally, the ultrasound treatment transducer comprises a full circular annular phased array.


Optionally, the ultrasound treatment transducer comprises a partial circular annular phased array.


Optionally, the ultrasound treatment transducer is configured to be directed and moved to guide therapeutic energy to the renal artery.


Optionally, the ultrasound treatment transducer comprises a two-dimensional array and is configured to move therapy focus by a three-dimensional electronic control mechanism to guide therapeutic energy to the renal artery.


Optionally, the ultrasound treatment transducer is configured to be moved by a mechanical control mechanism to guide therapeutic energy to the renal artery.


A method for imaging during delivery of a therapy, includes: acquiring an image of a body portion of a patient; identifying a region of an anatomical structure that has a relationship to a target tissue in the image; tracking a location and/or a feature of the region of the anatomical structure in the image; integrating results from the act of tracking; generating a template library to cover possible changes of the location and/or changes of the feature of the region of the anatomical structure; and delivering the therapy to the target tissue while tracking the region of the anatomical structure in the image.


Optionally, the method further includes continuously delivering therapy to the target tissue despite a change in one or more locations and features of the region of the anatomical structure.


Optionally, the act of tracking occurs in response to a change in the location or the feature of the region of the anatomical structure.


Optionally, the region of the anatomical structure comprises the target tissue.


Optionally, at least one of breathing, blood flow, conscious movement, or unconscious movement of the patient changes the location and/or the feature of the region of the anatomical structure.


Optionally, the region of the anatomical structure is undetectable by the imaging module as a result of at least one of breathing, blood flow, conscious movement, and unconscious movement.


Optionally, the method further includes stopping imaging of the body portion of the patient when the region of the anatomical structure is undetectable.


Optionally, the method further includes automatically re-detecting the region of the anatomical structure location or feature.


Optionally, the automatically recovering step further comprises automatically recovering the region of the anatomical structure location or feature by first determining a last known location or feature of the region of the anatomical structure in the image.


Optionally, the act of tracking occurs in less than 5 milliseconds.


Optionally, the act of delivering the therapy comprises denervating renal nerves surrounding the renal artery.


Optionally, the act of delivering comprises delivering ultrasound to the target tissue.


Optionally, the act of tracking comprises using a B-mode image, Harmonic Imaging, or 3D ultrasound imaging.


Optionally, the act of tracking comprises using a color Doppler image, a color power Doppler image, or a directional color power Doppler mode image.


Optionally, the act of tracking comprises using an image in B-mode, Harmonic mode, color Doppler mode, color power Doppler mode, a combination of the B-mode, the Harmonic mode and the color Doppler mode.


Optionally, the method further includes filtering the image to obtain a filtered image, such that the anatomical structure can be tracked in the filtered image.


Optionally, the method further includes determining if a pre-existing template matches a result from the act of tracking.


Optionally, the method further includes determining if a result from the act of tracking should be updated as a new template.


Optionally, a position of the target tissue is based on the pre-existing template and a new template. For example, averaging (e.g., weighted averaging, non-weighted averaging) may be performed using information in the pre-existing template and the new template to determine the position of the target tissue.


Optionally, the method further includes generating a new template when a pre-existing template does not match a result from the act of tracking, wherein the new template defines or indicates a location and a shape of the target tissue.


A method for treatment includes: acquiring with an imaging module an image of a body portion of a patient; identifying a region of an anatomical structure that has a relationship to a target tissue in the image; tracking a location and/or a feature of the region of the anatomical structure in the image; transforming a target position of the target tissue from an imaging space associated with the imaging module to a treatment space associated with a therapy module through one or more position sensors and a transmitter; and delivering a therapy with the therapy module to the target tissue while tracking the region of the anatomical structure.


Optionally, the one or more position sensors and the transmitter are configured to link a position of an imaging transducer of the imaging module to a position of an ultrasound treatment transducer of the therapy module.


Optionally, the one or more position sensors comprises a magnetic sensor, an optical sensor, an ultrasound sensor, or a mechanical position sensor.


Optionally, the one or more position sensors are mounted on an imaging transducer of the imaging module.


Optionally, the transmitter is mounted on an imaging transducer of the imaging module.


Optionally, the one or more position sensors are mounted on an ultrasound treatment transducer of the therapy module.


Optionally, the transmitter is mounted on an ultrasound treatment transducer of the therapy module.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 illustrates a system for tracking a target tissue and delivering therapy to a target tissue, in accordance with a preferred embodiment;



FIG. 2 illustrates a tracking algorithm, in accordance with a preferred embodiment;



FIGS. 3A and 3B illustrate images used for tracking and delivery of therapy to a target tissue, in accordance with a preferred embodiment;



FIG. 4 illustrates a flow chart for the functioning of a tracker, in accordance with a preferred embodiment;



FIG. 5 illustrates a tracker algorithm, in accordance with a preferred embodiment;



FIG. 6 illustrates a flow chart for the functioning of a detector, in accordance with a preferred embodiment;



FIG. 7 illustrates a detector algorithm, in accordance with a preferred embodiment;



FIG. 8 illustrates a flow chart for the functioning of an integrator, in accordance with a preferred embodiment;



FIGS. 9A and 9B illustrate a system including a filter for tracking a target tissue and delivering therapy to a target tissue, in accordance with a preferred embodiment;



FIG. 10 illustrates a therapy module, in accordance with a preferred embodiment;



FIG. 11 illustrates a system including an imaging and therapy module, in accordance with a preferred embodiment;



FIGS. 12A and 12B illustrate an interleaving and a continuous mechanism for imaging and therapy delivery, respectively, in accordance with first and second preferred embodiments; and



FIG. 13 illustrates a method of tracking a target tissue and delivering therapy to a target tissue, in accordance with a preferred embodiment.





DETAILED DESCRIPTION

The following description of the preferred embodiments of the invention is not intended to limit the invention to these preferred embodiments, but rather to enable any person skilled in the art to make and use this invention. Disclosed herein are systems and methods for identifying at least one anatomical structure and tracking the motion of the at least one anatomical structure using imaging before and during delivery of a therapy to a patient.


Described herein are systems and methods for tracking an anatomical structure in a patient and delivering therapy to an anatomical structure. The structure receiving the delivered therapy from the system is the target tissue. In some embodiments, the system may function completely non-invasively. Alternatively, the system may additionally include catheterization or otherwise surgically manipulating the patient. The system may be used to track an anatomical structure, such as an organ, blood vessel, artery, bone, blood, or any other type of anatomical structure. For example, in some embodiments, the system may function to track a kidney or renal artery of a patient. Alternatively, the system may be used to track a region of an anatomical structure, such as a curved edge or surface, a more distal or proximal portion of an organ, blood flow through a vessel, a distinguishing feature of an organ, for example glomeruli of the kidney, or any other region of interest of an anatomical structure. In some embodiments, a feature of an anatomical structure may be tracked, such as a location, shape, intensity, contrast, density, or otherwise characteristic of the anatomical structure. The location of an anatomical structure may include an x, y coordinate or an x, y, z coordinate. Alternatively, the location of the anatomical structure may be tracked in a two-dimensional plane or in three-dimensional space. The tracked anatomical structure may be a different structure than the anatomical structure receiving therapy from the system, such that a change in location or feature of the anatomical structure indicates a change in position of the target tissue. Alternatively, the anatomical structure may be the same as the target tissue, such that the target tissue is the anatomical structure that is being tracked. In some embodiments, the tracked anatomical structure may be a kidney and the target tissue receiving therapy may be a renal artery.


In some embodiments, the system may deliver therapy via ultrasound, mechanical vibrations, electromagnetic waves, lasers, X-ray or any other type of non-invasive radiation therapy. The therapy may include renal denervation, kidney stone disruption, gallstone disruption, bile duct stone disruption, ureter stone disruption, or any other type of non-invasive therapy.


In general, an anatomical structure may be lost and/or move during tracking and/or while receiving therapy. For example, an anatomical structure may be lost due to a shadow from another organ or bone structure, for example the rib cage. Alternatively or additionally, an anatomical structure may move due to breathing, blood flow, conscious movement, or unconscious movement of the patient during the procedure. In some instances, the region of the anatomical structure may become undetectable by the system as a result of breathing, blood flow, conscious movement, or unconscious movement of the patient. For example, an anatomical structure may move approximately 2 cm/second. In some instances, the anatomical structure may move substantially in a plane parallel to the plane of the system, or principal plane. Alternatively, the anatomical structure may move perpendicularly or variably relative to the system. As described herein, the system is configured to track a region of an anatomical structure despite shadows or deep breathing by a patient that moves an anatomical structure out of sight.


In some embodiments, the system may utilize an imaging module to locate the target tissue and track the position and/or movements of the target tissue, such that the therapy module can maintain its focus on the target tissue during the treatment process. In some embodiments, the imaging information may be used to confirm that the focus of the therapy module is properly positioned over the treatment region. The system then calculates the treatment parameter, such as dosing of ultrasound energy to be applied to the treatment region. For example the physician may enter the desired dosing level for a particular treatment. The system may also take into account other parameters, such as the distance of the target region from the therapy module, and calculate the appropriate ultrasound energy to apply to achieve the desired dosing at the target region. A particular treatment plan, such as a specific treatment pattern (e.g., energizing multiple spots within a treatment area), and a specific dosing routine (e.g., spreading a dose into multiple quantized delivery over a finite period of time to achieve the desired dose) may be selected. The system may then implement the treatment plan, and ultrasound energy may be delivered to the treatment region based on the treatment plan. In some embodiments, the treatment plan includes sequential lesions offset from the blood flow of a vessel and within 5 mm of one another. In another embodiment, the treatment plan includes sequential lesions offset from the blood flow and within 1 mm of each other. In another embodiment, the sequential lesions do not have an offset from one another and sequential lesions are applied atop one another in substantially the same position.



FIG. 1 illustrates a system 100 for tracking a region of an anatomical structure and delivering therapy to a target tissue, in accordance with a preferred embodiment. The system according to FIG. 1 preferably functions to image one or more anatomical structures, track a location or a feature of the anatomical structure, and delivery therapy to a target tissue. As shown in FIG. 1, a system 100 for identifying at least one anatomical structure and tracking the motion of the at least one anatomical structure using imaging before, during, or after delivery of a therapy to a patient includes an imaging module 101 and a therapy module 102. The imaging module 101 may be configured to acquire an image, identify one or more locations and/or features of an anatomical structure in the image, and/or track a location and/or feature of the anatomical structure within the image. The therapy module 102 of the system 100 may be configured to deliver therapy to a target tissue


In some embodiments, the therapy module 102 may include a therapy energy delivering subsystem 107, which functions to generate controlled electrical energy to the ultrasound treatment transducer 108. In some embodiments, the ultrasound treatment transducer 108 transmits the ultrasound energy into the targeted tissue structure in a human body. In some embodiments, the ultrasound treatment transducer 108 may be a full circular annular phased array transmitting the focused ultrasound energy along the acoustic axis in depth direction into the targeted tissue structure in a human body. In other embodiments, the ultrasound treatment transducer 108 may be a section of full (e.g., partial) circular annular phased array transmitting the focused ultrasound energy along the acoustic axis in depth direction into the targeted tissue structure in a human body. For example, the transducer may have a pie shape so that the shape is less than a full circular shape. In some embodiments, the therapy module 102 may include a tip/tilt motion control unit 109 that adjusts the ultrasound treatment transducer rotation in tip and tilt directions to follow the targeted tissue motion. In other embodiments, the following of the targeted tissue motion may be accomplished by electronic control of the phasing of the ultrasound elements in the ultrasound treatment transducer, thereby obviating the need to mechanically move the ultrasound treatment transducer. In further embodiments, the control of the ultrasound energy focus may be accomplished using both electronic phasing control of ultrasound elements in the ultrasound transducer 108 and mechanical control of the movement of the ultrasound transducer 108 by the therapy module 102. In some cases, such technique may allow control of ultrasound energy focus at any position within a huge treatment volume in 3D space. In some embodiments, the therapy module 102 may further include a transmitter and/or one or more position sensors of a 3D position system 110.


In some embodiments, the imaging module 101 may include an image acquisition subsystem 103 that functions to acquire an image. In some embodiments, the image acquisition subsystem 103 may use ultrasound to acquire images of a region of an anatomical structure. In some embodiments, the imaging module 101 may further include an image tracking system 104 that functions to track a location and/or feature of an anatomical structure within the image acquired by the image acquisition subsystem 103. In some embodiments, the imaging module 101 may include an ultrasound imaging transducer 105 that transmits the ultrasound signals into the human body and receives the reflected signal from the tissue structures. In some embodiments, the imaging module 101 may further include position sensors 106 that are attached to the imaging transducer 105 to acquire the position of the imaging transducer 105 in 3D space and feed the position information to the imaging tracking subsystem 104. In some embodiments, the imaging transducer 105 may be linear, curved linear, phased, annular, or other types of imaging arrays that acquire an imaging plane inside a human body. In some embodiments, the imaging transducer 105 may be a two-dimensional array that acquires 3D ultrasound images inside a human body.


In some embodiments, the 3D position system determines the position of the ultrasound treatment transducer 108 and the relationship of the positions between the imaging transducer 105 and ultrasound treatment transducer 108. In some embodiments, an imaging ultrasound transducer 105 may be included near the therapy module 102, such that images may be acquired of the region of the anatomical structure being targeted, tracked, and treated as will be described below.


In some embodiments, the imaging module may acquire an ultrasound image. For example the imaging module may use echoes of ultrasound pulses to delineate objects or areas of different density in the body. A frequency range used may be between 0.5 to 18 megahertz or up to 50 or 100 megahertz. Alternatively, x-ray, computed tomography, magnetic resonance, or any other type of imaging modality, optical or otherwise, may be used. In some embodiments, the imaging of an anatomical structure may be acquired in a B-mode image, Harmonic image, a color Doppler image, a color power Doppler image, a directional color power Doppler mode image, any other type of image, or any combination of two or more of the foregoing. For example, in a B-mode image and/or Harmonic image, the system may image a two-dimensional cross-section of the tissue. Alternatively or additionally, the system may utilize color Doppler imaging, an imaging technique that combines anatomical information derived using ultrasonic pulse-echo techniques with velocity information derived using ultrasonic Doppler techniques to generate color-coded maps of tissue velocity superimposed on grey-scale images of tissue anatomy. Further, color power Doppler imaging has increased intensity and the added benefit of depicting flow in small vessels.


In some embodiments, the imaging module 101 may function to identify a position of a region of an anatomical structure, such that the therapy module 102 may deliver therapy in a substantially continuous manner to the target tissue. The imaging module 101 may rapidly identify the position of the target tissue such that the therapy module 102 may then rapidly deliver therapy to the target tissue. In an interleaving pattern, the position may be identified, followed by therapy delivery, followed by position identification, and so on. This interleaving pattern of the imaging module and therapy module may occur in rapid, repetitive succession such that therapy is delivered substantially continuously. The rapid, repetitive succession is required, such that the target tissue may be tracked substantially continuously and the therapy may be delivered substantially continuously.


In some embodiments, the imaging module 101 may function rapidly, such that a dose of therapy may be delivered substantially continuously to the target tissue without significant delay between identifying a position of the target tissue and delivering therapy to the target tissue or between subsequent doses of therapy to the target tissue. For example, the imaging module 101 may identify one or more locations and/or features of the region of the anatomical structure in less than 10 seconds, 5 seconds, 3 seconds, 2 seconds, or 1 second. Alternatively, the imaging module may identify one or more locations and/or features of the region of the anatomical structure in less than 1000 milliseconds, 750 milliseconds, 500 milliseconds, 250 milliseconds, 100 milliseconds, 75 milliseconds, 50 milliseconds, 25 milliseconds, 10 milliseconds, 5 milliseconds, or 1 millisecond. In some embodiments, the imaging module may use a frame rate of greater than or equal to 20 Hz. Alternatively, the imaging module may use a frame rate of less than 20 Hz.


Returning to FIG. 1, in some embodiments, the image tracking subsystem 104 of imaging module 101 includes a tracker and a detector. Both the tracker and detector are computer algorithms configured to identify and track a shape, location, and/or feature of a region of an anatomical structure in an image by searching within a region of interest in the image for a shape, location, and/or feature of the region of the anatomical structure. As described below in further detail, the imaging module 101 may weigh results from the tracker and detector differentially, such that in some instances only the tracker results may be used or, alternatively, only the detector results or both. In some embodiments, the tracker and detector may each independently identify and track a shape, location, and/or feature of a region of an anatomical structure in an image. The tracker and detector may identify motion of a region of an anatomical structure and compensate for the motion by adjusting the focal point, such that therapy may be delivered substantially continuously to a target tissue. In some embodiments, a system may use both a tracker and detector to identify and track a region of an anatomical structure in an ultrasound image. The tracker and the detector complement each other, increase robustness of the system, and compensate for non-uniformity of ultrasound waves (as compared to imaging with light) in their interactions with an object or tissue being imaged.


In some embodiments, the tracking capabilities of the tracker and detector may be combined into one algorithm, negating the need for a separate tracker and detector. In some embodiments, results from the tracker and detector may be compared to templates, which identify a previous shape, location, and/or feature of the region of the anatomical structure. For example, the tracker may be a short-term detector in that the results are compared to several previous image (In-p, In-p-1, - - - In-3, In-2, In-1) and use weighted function to obtain the final position. In some embodiments, the tracker will first look for change near the previous location (i.e. previous image (In-1)) rather than looking throughout the entire image. Further for example, the detector may be a long-term detector in that the results are compared to more than one template (i.e. a template pool) from any number of previous images. In some embodiments, the long-term template management samples breathing cycles. In general, the combination of the complimentary tracker and detector will enable the system to compensate automatically, without user intervention, if the target becomes lost or unfocused. Alternatively, any quantity and/or type of trackers and/or detectors may be used. In some embodiments, the system may include additional trackers and/or detectors such that the additional trackers and/or detectors complement the existing trackers and detectors for tracking a region of an anatomical structure. In some embodiments, the multiple complementary trackers and/or detectors may lead to an increased computation time and/or memory requirements, however the robustness of the system will also improve. In some embodiments, the system 100 further includes an integrator. The integrator is an algorithm configured to compare and/or integrate the results from tracker and detector of the image tracking subsystem of the imaging module 101 and direct the therapy module 102 to deliver the therapy to the target tissue.


The tracker and detector are algorithms for determining a location and/or feature of a region of an anatomical structure. In some embodiments, as shown in FIG. 2, a feature histogram algorithm may be used. Feature histogram describes the two-dimensional spatial distribution of the featured pixels in a defined area or analysis region 201. As shown in FIG. 2, the analysis region 201 may be equally divided into several smaller regions. The analysis region 201 containing 6 by 6 pixels, as shown in FIG. 2, is subdivided into 4 sub-regions 202, which contains 3 by 3 pixels 203. However, it should be understood that any number of pixels in analysis region 201 may be used, for example less than 36 pixels or more than 36 pixels. For example, a 5×5, 75×75, 100×100, 500×500, or 1000×1000 pixels, or anything above, below or in-between may be utilized.


In some embodiments, as shown in FIG. 2, a pixel 203 of an anatomical structure may be identified, for example by contrast, pixel density, or intensity, in the analysis region 201, denoted by an “x” in the pixel 203. Each “x” or pixel feature may be totaled for each sub-region, resulting in a 2 by 2 feature histogram 204 of region 201. The 2 by 2 feature histogram 204 is further normalized into a 2 by 2-normalized feature histogram 205. The distribution of the feature histograms indicates a location or feature of the region of the anatomical structure. However, it should be understood that any number of histogram dimension can be used, for example 4 by 4, 8 by 8, 8 by 4, 4 by 8, 16 by 16, 16 by 8, 8 by 16, 32 by 32 or any other number.


In some embodiments, a first feature histogram indicating a first location or feature of a region of an anatomical structure may be compared to second feature histogram indicating a second location or feature of the region of the anatomical structure. In some embodiments, the first or second feature histogram may include a template from a previous image. The two histograms may be compared using equation (1) below, where H1ij is the first feature histogram, H2ij is the second feature histogram, N is the total number of bins in the x-direction of the 2D feature histogram, M is the total number of bins in the y-direction of the 2D feature histogram, and D is the distance between the two histograms between 0 and 1. When D=0, the two histograms are identical. Conversely, when D=1, the two histograms are the most different.









D
=


1
-




i
=
1

N






j
=
1

M





H
1
ij



H
2
ij











(
1
)







In some embodiments, alternative algorithms may be employed, such as sum squared difference, sum absolute difference, or normalized cross correlation (NCC). For example, in NCC, a position of the region of the anatomical structure is determined by a pixel-wise comparison of the current image with the template containing a previous position of the region of the anatomical structure. The search region in the template is shifted in discrete steps in the N and M directions, and then the comparison is calculated (i.e. subtracting the mean and dividing by the standard deviation at every step) over the template search area for each position. The position of the maximum NCC values indicates the position of the region of the anatomical structure in the current image. Alternatively, any other threshold NCC value (i.e. minimum) may be used.



FIGS. 3A and 3B illustrate a region of an anatomical structure that is being tracked by two tracking boxes 302, 303 working on different tissue areas, in and around a region 301 that is viewable by a user. Each tracking box is associated with its own tracker, detector, and integrator. As shown in FIG. 3, two tracking boxes 302, 303 are used to increase the robustness and fidelity of the system, such that both the first and second tracking boxes are tracking a similar region of the anatomical structure in each of the tracking boxes 302, 303. Tracking is not completely lost and therapy is not stopped unless both boxes lose tracking. For example, if the first tracking box (associated with tracker, detector, and integrator) becomes lost and/or is unable to find the region of the anatomical structure, the second tracking box (associated with tracker, detector, and integrator) will continue tracking the region of the anatomical structure and therapy delivery will continue and vice versa.


In this example, the tracking boxes are tracking a location or feature of a region of an anatomical structure in two images, at opposite ends of a breathing cycle, using a feature histogram algorithm, as described above. For example, a beginning of a breathing cycle is shown in FIG. 3A and an end of a breathing cycle is shown in FIG. 3B. The crosshairs 304 indicate a target region or tissue for receiving therapy. As shown in FIG. 3, the target tissue (e.g. renal artery) receiving therapy is distinct from the regions of the anatomical structure (e.g. tissue) that is being tracked by the tracking boxes. In some embodiments, the search region may be any size, for example 361 pixels by 420 pixels. Alternatively, the search region may be larger than 361 pixels by 420 pixels or less than 361 pixels by 420 pixels. The tracking boxes 302, 303 may be any size, for example 64×64 pixels. Alternatively, the tracking boxes may be less than 64×64 pixels or greater than 64×64 pixels. In some embodiments, a user may select the tracking box size. Alternatively, the tracking box size may be selected automatically by the system. Alternatively, only one tracking box or more than two tracking boxes may be used. In some embodiments, the system may include additional tracking boxes to add redundancy to the system. In some embodiments, the multiple complementary trackers and/or detectors may lead to an increased computation time and/or memory requirements, however the robustness of the system will also improve.


In some embodiments, the tracking performed by the first and second tracking boxes may occur with an accuracy of root-mean-square (RMS) error of less than or equal to 2 mm. Alternatively, the RMS error may be more than 2 mm, but still within a suitable accuracy. In some embodiments where two tracking boxes are used, if both the tracking boxes 302, 303 are lost, the tracking boxes 302, 303 may recover at the same time and maintain the same relative position with error within less than or equal to 40 pixels. Alternatively, the error may be within more than 40 pixels. Further, in some embodiments, if the region of the anatomical structure moves outside of the image, the tracker and detector will cease to track the region of the anatomical structure.


In some embodiments, as shown in FIG. 4, a tracker may function as a short-term detector, as described above. The tracker may compare a feature histogram of a current location or feature of a region of an anatomical structure in a current image (In) to a template. In some embodiments, the template may be a feature histogram of a previous location or feature of the region of the anatomical structure in a previous image (Ln-1). In some embodiments, the tracker may search for a change in a region of the anatomical structure near a previous location of the region of the anatomical structure in the template instead of searching an entire template. The two feature histograms are compared, for example using equation (1), and the minimum distance D between the two feature histograms may be determined and the x, y coordinates of the point of the minimum distance D may be identified, as shown in FIG. 4. Alternatively, a maximum distance D or any other threshold may be used when comparing two or more feature histograms.


As shown in FIG. 5, within the search region 501, the tracker tracks a possible current location or feature 502 of a region of the anatomical structure in the current image (In). The previous location or feature (with M, N coordinates) of the region of the anatomical structure from image (Ln-1) is a temlate 503, as described above. In some embodiments, the tracker may search for a change in a region of the anatomical structure near a previous location of the region of the anatomical structure instead of searching the entire image. The distance between the feature histograms of the possible current location or feature 502 and the previous location or feature 503 of the region of the anatomical structure is calculated. Each of the distances may be represented by value D, such that the minimum D value and the position of the minimum D value indicate a best match between a current location or feature and a previous location or feature of the region of the anatomical structure in the template.


As shown in FIGS. 6 and 7, within the search region 701, the detector may function as a long-term detector, as described above. The detector may detect a possible current location or feature of a region of the anatomical structure in a current image (In). The feature histogram of the possible current location or feature 702 in a current image In is compared to a template pool 704 comprising feature histograms for one or more templates of previous locations and/or features, for example 703, of the region of the anatomical structure in previous images (In-1). For example, a template pool 704 may include a plurality of templates. As one example, the template pool 704 may include 64 templates. The feature histograms of the possible current location or feature 702 of a region of the anatomical structure are compared to the feature histograms of the one or more templates, for example 703, through calculating the D value. The template corresponding to the minimum D value and the position of the minimum D value indicates a best match between a current location or feature 702 and the template from the template pool 704, identifying the location or feature as the region of the anatomical structure 701, as shown in FIG. 7. In some embodiments, a maximum Normalized Cross Correlation (NCC) value may correspond to a best match between a current location or feature and the template from the template pool, which could replace the D value as described above.


In some embodiments, the feature histogram of the current image is compared to all templates in the template pool. Alternatively, the feature histogram of the current image may be compared to a subset of the template pool. In some embodiments, all templates search in their own search regions and the region of the anatomical structure is at the position, which gives the maximum (i.e. NCC value) or minimum value (i.e. sum squared difference value) in all search regions of the templates.



FIG. 8 illustrates an integrator flow chart. In some embodiments, as shown in FIG. 8, an integrator is an algorithm that compares the tracking results from the tracker and detector and determines (1) if the results from the tracker or detector should be used in determining a current location or feature of the region of the anatomical structure and (2) if the results from the tracker and detector should be added as a template to the template pool. In some embodiments, the integrator weighs the results of the detector more heavily. As shown in FIG. 8, if the results from the detector match with a key template, which is a template sampled throughout the motion cycles, then the integrator will use the detector results 802. Otherwise, if the distance value D determined by the detector is less than the distance value D determined by the tracker 803, the integrator will use the results from the detector 804, such that the smaller distance value D from the detector more accurately defines the feature histogram of the location or feature. Alternatively, if the distance value D determined by the detector is more than the distance value D determine by the tracker, then the integrator further evaluates the results from the tracker 805. If the distance value D is greater than a predetermined threshold or if the distance of the current location to the closest template location is greater than a predefined pixel distance (L), for example 3 √{square root over (2)} or any other distance, the feature histogram denoted by distance value D will be updated as a template and maintained as part of the template pool 807. In some embodiments, if the location of a current feature is a predefined distance (L) from all other templates in the pool, then the current feature will be saved as a “key” template. Any of the above integrations performed by the integrator may be sent to the therapy module, such that an x, y, z coordinate of the current location may be sent to the therapy module and the therapy module may deliver therapy to the target tissue, as shown in FIG. 8. In some embodiments, the time between the therapy module receiving instructions and delivering therapy is less than or equal to 50, 40, 30, 20, 10, 5, or 1 milliseconds. Alternatively, the time between receiving instructions and delivering therapy may be more than 50 milliseconds.


In some embodiments, as shown in FIG. 9A, a system 900 for tracking a region of an anatomical structure and delivering therapy to a target tissue may further include a filter 901. The filter may use an algorithm to reduce noise in the image (In), such that the imaging module 902 may determine one or more locations and/or features of the region of the anatomical structure in the image (In). In some embodiments, the noise may include speckle, multiple coherent reflections from the environment surrounding the region of the anatomical structure or target tissue, or any other type of noise. In some embodiments, the filtered image may be visible only to one of the tracker or detector. Alternatively, both the tracker and detector may use the filtered image. In some embodiments, a user of the system 900 may select between viewing the filtered image or an unfiltered image.


In some embodiments, as shown in FIG. 9B, a filter may use a simple moving average filter to remove noise in an image (In). As shown in FIG. 9B, each region 903 of the image may be identified (in) and the average intensity of the pixels in each region may be determined. Equation (2) may be used to smooth the image, such that y[i] equals the smoothed pixel intensity, M equals the number of regions 903 in the average, i equals the location of smoothed pixel, and j equals the index within the region. Alternatively, any other type of filtering equation may be used.










y


[
i
]


=


1
M






j
=
0


M
-
1




x


[

i
+
j

]








(
2
)







In some embodiments, where the integrator integrated the results from the tracker and detector, as described above with respect to FIG. 8, the therapy module may receive a current target tissue location and a distance to the current target tissue location from the integrator. In some embodiments, the therapy module 1000 may include one or more ultrasound transducers 1001, 1002, as shown in FIG. 10. The therapy module 1000 may include a phased or fixed array of ultrasound transducers 1002 for delivering therapy to the target tissue. Further, in some embodiments, as shown in FIG. 10, the therapy module may include a second phased or fixed array of ultrasound transducers 1001 for acquiring images of the region of the anatomical structure. The region of the anatomical structure may then be tracked in the image by the tracker and detector, as described above. As shown in FIG. 11, the therapy module 1000 may be integrated into a patient platform 1030, such that the therapy module 1000 is positioned in a cavity 1010 of the patient platform 1030 while maintaining access to a patient lying on the patient platform 1030. In some embodiments, the imaging module 1020 may be in the same room and/or electrically connected to the patient platform 1030 and/or the therapy module 1000. Alternatively, the imaging module 1020 may be in communication with the therapy module 1000 through Bluetooth, Wi-Fi, or any other type of connection. Other features and aspects of the system 1050 of FIG. 11 are disclosed in PCT Application Serial Number 2014/022141, which is herein incorporated by reference.


In some embodiments, the ultrasound transducer of the therapy module may be moved, repositioned, or otherwise relocated by a motion control mechanism. Alternatively, the ultrasound transducer of the therapy module may be directed and moved to guide therapeutic energy to the target tissue, for example by an applicator 1060. In some embodiments, the ultrasound transducer of the therapy module may be moved by a three-dimensional electronic beam steering control mechanism to guide therapeutic energy to the target tissue. Alternatively, the ultrasound transducer of the therapy module may be moved by a mechanical control mechanism to guide therapeutic energy to the target tissue.


In some embodiments, as shown in FIG. 12A, the imaging module and therapy module may function in rapid succession in an interleaving mechanism. FIG. 12A illustrates the interleaving pattern with solid arrows representing hard sync triggers and dashed arrows representing soft sync triggers. The interleaving pattern, as shown in FIG. 12A, may continue until the prescribed dose of therapy has been delivered. In some embodiments, the therapy module will be re-targeted to a new lesion or position and the interleaving mechanism will resume. Alternatively, in some embodiments, the imaging module and therapy module may function simultaneously, such that therapy is continuously being delivered while the imaging module is transmitting tracker and detector results to the therapy module, as shown in FIG. 12B. Alternatively or additionally, the therapy module may function using a predictive mechanism, such that the therapy module may predict a future position of the region of the anatomical structure that is being tracked by the imaging module from several previous target positions and move to that predicated position to deliver therapy.



FIG. 13 illustrates a method of tracking a target tissue and delivering therapy to a target tissue, in accordance with a preferred embodiment. As shown in FIG. 13, a method for imaging during delivery of a therapy of a preferred embodiment includes the steps of acquiring an image of a body portion of a patient S100; identifying a region of an anatomical structure that has a relationship to a target tissue in the image S110; tracking a location or feature of the region of the anatomical structure in the image S120; integrating the results from the tracking S130; generating a unique template library to cover possible changes of the one or more locations and features of the region of the anatomical structure S140; determining if a pre-existing template matches a result from the tracking or if the result should be updated as a new template, wherein the pre-existing template and the new template define a position of the target tissue in the image S150; and delivering the therapy to the target tissue while tracking the region of the anatomical structure in the image S160. In some embodiments, the method preferably functions to track a region of an anatomical structure, such that the position of the anatomical structure correlates with a position of a target tissue. The method may be used for delivering ultrasound to denervate a renal artery but, additionally or alternatively, can be used for any suitable applications, clinical or otherwise. For example, the method may be used to deliver ultrasound to a kidney, gallbladder, bile duct, or ureter to disrupt kidney, gallstones, bile duct stones, or ureter stones, respectively.


As shown in FIG. 13, step S100 includes acquiring an image of a body portion of a patient. Step S100 preferably functions to image a region of an anatomical structure of a patient, such that a location and/or feature of a region of the anatomical structure may correspond to a position of the target tissue for receiving therapy. As described above, the image may be acquired in B-mode, Harmonic image, color Doppler, color power Doppler, or directional color power Doppler mode image. In some embodiments, the imaging may be performed using ultrasound or any other type of imaging modality, optical or otherwise.


As shown in FIG. 13, step S110 includes identifying a region of an anatomical structure that has a relationship to a target tissue in the image. Step S110 preferably functions to identify a region of an anatomical structure that moves, deforms, or otherwise tracks in a similar manner as the target tissue, such that the anatomical structure may be tracked while the target tissue is receiving therapy. For example, if the target tissue moves 2 cm to the right in the image, the region of the anatomical structure being tracked should also move 2 cm to the right. In some embodiments, the target tissue is the anatomical structure being tracked.


As shown in FIG. 13, step S120 includes tracking a location or feature of the region of the anatomical structure in the image. Step S120 preferably functions to track a location or feature of a region of the anatomical structure using a tracker and detector, such that the therapy module may be notified of a change in location or feature of the target tissue. In some embodiments, step S120 occurs in response to a change in location or feature of the region of the anatomical structure.


As shown in FIG. 13, step S130 includes integrating the results from the tracking with the tracker and detector. Step S130 preferably functions to determine if the results from the tracker and detector will be used and if a new template should be generated based on the results from the tracker and detector. For example, if the tracking results from the tracker and detector, respectively, match a key template, as described above, the integrator will use the detector results and instruct the therapy module to deliver therapy to the target tissue, such that a position of the target tissue is known by the integrator and transmitted to the therapy module.


As shown in FIG. 13, step S140 includes generating a unique template library to cover possible changes of the one or more locations and features of the region of the anatomical structure. Step S140 preferably functions to maintain a template pool of possible locations and/or features of the anatomical structure being tracked by the imaging module, such that the template pool was generated over time from previous images. Each result from the tracker and detector may be compared to the template pool to determine if 1) the result matches a template and thus the template can inform the therapy module as to the position of the target tissue or 2) the result does not match a template and a new template needs to be generated and thus the new template can inform the therapy module as to the position of the target tissue, as further recited in S150.


As shown in FIG. 13, step S160 includes delivering the therapy to the target tissue while tracking the region of the anatomical structure in the image. Step S160 preferably functions to deliver therapy to the target tissue while consistently aligning an orientation, position, or otherwise direction of the therapy module with the target tissue. The therapy module, as described herein, receives information from the imaging module that pertains to a position of the target tissue, such that the tracker and detector track a position of the target tissue by tracking a region of an anatomical structure.


In some embodiments, the method of FIG. 13 further includes substantially continuously delivering therapy to the target tissue despite a change in one or more locations and features of the region of the anatomical structure. The therapy module may continue delivering therapy despite a change since the imaging module may alert, notify, or otherwise inform the therapy module of the change, and the therapy module may adjust accordingly.


In some embodiments, the method of FIG. 13 further includes stopping the imaging of the region of the anatomical structure when the region of the anatomical structure is undetectable. For example, the anatomical structure may move perpendicularly away from the imaging plane, such that the region of the anatomical structure is undetectable. In some embodiments, the imaging module may automatically recover (e.g. without user intervention) the region of the anatomical structure location or feature, such that therapy delivery may resume. Further, automatically recovering the region of the anatomical structure location or feature may occur by first determining a last known location or feature of the region of the anatomical structure in the image (logic function). In some embodiments, the last known location or feature may correspond to a template from the template pool.


In some embodiments, the method of FIG. 13 further includes filtering the image, such that the anatomical structure can be tracked in the filtered image. The image may be filtered using a moving average filter or any other type of filter.


In some embodiments, the method of FIG. 13 further includes generating a new template when the pre-existing template does not match the tracking results, such that the new template corresponds to a position of the target tissue in the image. In some embodiments, the new template is assigned as the key template, as described above. In some embodiments, the new template may be generated by the integrator.


In some embodiments, the method of FIG. 13 is implemented in a graphics processing unit (GPU), FPGA, and/or DSP to further reduce the computation time of the tracker, detector and integrator.


As described herein, a method for treatment includes: acquiring with an imaging module an image of a body portion of a patient; identifying a region of an anatomical structure that has a relationship to a target tissue in the image; tracking a location and/or a feature of the region of the anatomical structure in the image; transforming a target position of the target tissue from an imaging space associated with the imaging module to a treatment space associated with a therapy module through one or more position sensors and a transmitter; and delivering a therapy with the therapy module to the target tissue while tracking the region of the anatomical structure. In some embodiments, the act of transforming is performed to bring a target position of the target tissue (e.g., renal artery) in the imaging space (e.g., ultrasound imaging coordinate) to a transformed target position in the treatment space (e.g., therapeutic array coordinate). Various techniques may be employed to achieve such objective. For example, in some cases, a real-time electromagnetic tracking system with sub-millimeter and sub-degree accuracy may be used. The magnetic field sensor may be attached on the handle of the imaging transducer, and a magnetic field transmitter may be attached to the base of therapeutic treatment module. The magnetic field transmitter generates a magnetic field. When the magnetic sensor is placed inside controlled, varying magnetic fields generated from the transmitter, voltage are induced in the sensor coils. These induced voltages can be used by the measurement system to calculate the position and the orientation of the magnetic field sensor in 3D space. In such cases, after the renal artery target position is detected by ultrasound imaging (in image coordinate), the transformation of the position may be performed as follows: 1) the treatment position and orientation of a target in the image coordinate are linked with the magnetic field sensor position and orientation based on mechanical design and calibration (in magnetic sensor coordinate); 2) the target position and orientation in the magnetic sensor coordinate are then transformed into the treatment module coordinate by the detection of the sensor position and orientation in the magnetic field generated by the magnetic field transmitter, and 3) the target position and orientation in the treatment module coordinate are further transformed into the coordinate of the therapeutic array. In some cases, the third transformation above is not needed if the coordinate frame of the therapeutic array is aligned with the treatment module coordinate frame. Therefore, knowing the position and orientation of the imaged target relative to the coordinate frame of the therapeutic array through the above transformations, the therapeutic system can adjust the mechanical movement of the therapeutic array and/or the phases of the array elements to deliver the ultrasound energy at the imaged treatment target.


In other embodiments, non-magnetic position measurement system may be used. This has the advantage of eliminating the possibilities of wrong targeting when a metal object gets close to the magnetic sensor and the transmitter. For example, in other embodiments, optical position measurement system may be used that measures the 3D positions of either active or passive markers affixed to application-specific tools. In one implementation, three different optical tool plates with at least three optical markers on each plate may be provided. One plate with optical markers is attached with the handle of the imaging transducer. The other two plates are attached on the left and right sides of the therapeutic treatment module separately. An optical position sensor system may be attached to the base of therapeutic treatment module. The optical position sensor system emits infrared (IR) light from its illuminators, similar to the flash on a conventional camera. The emitted IR light reflects back to the Position Sensor off markers (which may be spherical or semi-spherical) on the passive tool plates. The optical position sensor system then measures the positions of the markers and calculates the positions and orientations of the tool plates. The relationship of both positions and orientations between the tool plate attached to the imaging transducer (e.g., the handle) and the treatment module can be determined by the position sensor system at a rate of 20 Hz in real-time. To further optimize the detection accuracy of the positions and orientations between the imaging transducer and treatment module, the two plates which are attached along the left and right side of the treatment module are orientated to the optimized angles for treating the right and left renal denervation separately. In such cases, after the renal artery target position is detected by ultrasound imaging (in image coordinate), the transformation of the positions and orientations of the treatment target from the imaging coordinate to the therapy coordinate may be performed as follows: 1) the target position and orientation in the image coordinate are linked with the optical plate position (of the imaging transducer) based on mechanical design and calibration (to obtain treatment position and orientation in imaging tool plate coordinate); 2) the target position and orientation in the imaging tool plate coordinate are further transformed into optical position sensor coordinate frame; 3) the target position and orientation in the position sensor coordinate frame are then transformed into either left or right tool plate coordinate frame attached on the treatment module depending on the treatment of right or left side renal nerves; 4) the target position and orientation in the left/right treatment tool plate coordinate frame are further transformed to the therapeutic array coordinate frame based on mechanical design dimension and calibrations. Thus, the therapeutic system may control the therapeutic array to deliver the ultrasound energy to the treatment target through the above transformations by adjusting the mechanical movement of the therapeutic array and/or electronic phasing steering (e.g., in depth direction, and/or other direction(s)).


The systems and methods of the preferred embodiment and variations thereof can be embodied and/or implemented at least in part as a machine configured to receive a computer-readable medium storing computer-readable instructions. The instructions are preferably executed by computer-executable components preferably integrated with the imaging module and/or the therapy module. The computer-readable medium can be stored on any suitable computer-readable media such as RAMs, ROMs, flash memory, EEPROMs, optical devices (e.g., CD or DVD), hard drives, floppy drives, or any suitable device. The computer-executable component is preferably a general or application-specific processor, for example Versatile Data Acquisition System (VDAS), but any suitable dedicated hardware or hardware/firmware combination can alternatively or additionally execute the instructions.


In other embodiments, instead of or in addition to using histogram(s), a feature matching technique such as Normalized Cross Correlation method, Sum Square Difference method, Sum Absolute Difference method, etc., may be used.


The examples and illustrations included herein show, by way of illustration and not of limitation, specific embodiments in which the subject matter may be practiced. Other embodiments may be utilized and derived therefrom, such that structural and logical substitutions and changes may be made without departing from the scope of this disclosure. Such embodiments of the inventive subject matter may be referred to herein individually or collectively by the term “invention” merely for convenience and without intending to voluntarily limit the scope of this application to any single invention or inventive concept, if more than one is in fact disclosed. Thus, although specific embodiments have been illustrated and described herein, any arrangement calculated to achieve the same purpose may be substituted for the specific embodiments shown. This disclosure is intended to cover any and all adaptations or variations of various embodiments. Combinations of the above embodiments, and other embodiments not specifically described herein, will be apparent to those of skill in the art upon reviewing the above description.

Claims
  • 1. A system for identifying at least one anatomical structure and tracking a motion of the at least one anatomical structure using imaging before and during delivery of a therapy to a patient, the system comprising: an imaging module configured to identify a location and a feature of a region of the anatomical structure in an image, wherein the imaging module comprises a tracker, a detector, and an integrator, wherein the tracker comprises a short-term detector configured to compare the feature of the region of the anatomical structure in a portion of the image to the portion in one or more previous images to generate a first input, wherein the detector comprises a long-term detector configured to compare the image to previous images in a template pool to generate a second input, and wherein the integrator is configured to obtain the first input from the tracker and the second input from the detector, and provide a positional data based at least in part on the first input from the tracker and/or the second input from the detector; anda therapy module comprising an ultrasound treatment transducer configured to deliver the therapy to a target tissue in the patient and to adjust delivery of ultrasound based on the positional data.
  • 2. The system of claim 1, wherein the imaging module is configured to, in real-time, track the anatomical structure using a feature identification technique.
  • 3. The system of claim 2, wherein the imaging module is configured to use a histogram of the anatomical structure in the image, or a feature matching technique.
  • 4. The system of claim 1, wherein the imaging module is configured to identify a location of the target tissue to be treated by the therapy module.
  • 5. The system of claim 1, wherein the tracker is configured to identify a new location or a new feature of the region of the anatomical structure in response to a change in the location and the feature of the region of the anatomical structure.
  • 6. The system of claim 1, wherein the detector is configured to identify a shape, a location, and a feature of the region of the anatomical structure.
  • 7. The system of claim 1, wherein the tracker, detector, and integrator are implemented in GPU, FPGA or DSP.
  • 8. The system of claim 1, wherein the therapy module is configured to function concurrently with the imaging module.
  • 9. The system of claim 1, wherein the therapy module is configured to deliver therapy to the target tissue despite a change in the location or the feature of the region of the anatomical structure without user intervention.
  • 10. The system of claim 1, wherein the anatomical structure comprises the target tissue.
  • 11. The system of claim 1, wherein at least one of breathing, blood flow, conscious movement, or unconscious movement of the patient changes the location and/or the feature of the region of the anatomical structure, wherein the image module is configured to determine a key template sampled throughout a motion cycle, and wherein the integrator is configured to use the detector results to direct the therapy module to deliver therapy to the target tissue if the results from the detector match with the key template.
  • 12. The system of claim 1, wherein the imaging module is configured to identify the location and the feature of the region of the anatomical structure in less than 1 second.
  • 13. The system of claim 1, wherein the imaging module is configured to identify the location and the feature of the region of the anatomical structure in less than 5 milliseconds.
  • 14. The system of claim 1, wherein the target tissue comprises a renal artery.
  • 15. The system of claim 1, wherein the ultrasound treatment transducer is configured to provide renal denervation.
  • 16. The system of claim 1, wherein the imaging module is configured to track the region of the anatomical structure is using a B-mode image, Harmonic image, or 3D Ultrasound imaging.
  • 17. The system of claim 1, wherein the imaging module is configured to track the region of the anatomical structure using a color Doppler image, a color power Doppler image, or a directional color power Doppler mode image.
  • 18. The system of claim 1, further comprising a filter, wherein the filter is configured to reduce noise in the image, such that the imaging module can determine the location and the feature of the region of the anatomical structure in the image.
  • 19. The system of claim 18, wherein the filter is configured to provide a filtered image that is visible to the tracker, the detector, or both the tracker and detector.
  • 20. The system of claim 18, further comprising a user interface for allowing a user to choose between viewing the filtered image or an unfiltered image.
  • 21. The system of claim 18, wherein the location is an x and y coordinate.
  • 22. The system of claim 18, wherein the location is an x, y, and z coordinate.
  • 23. The system of claim 1, wherein the image is an ultrasound image.
  • 24. The system of claim 1, wherein the integrator is configured to integrate results from the tracker and detector and direct the therapy module to deliver the therapy to the target tissue.
  • 25. The system of claim 1, wherein the location is in a plane.
  • 26. The system of claim 1, wherein the location is in a three-dimensional space.
  • 27. The system of claim 1, wherein a plane of movement of the anatomical structure is substantially parallel to an imaging plane of the imaging module.
  • 28. The system of claim 1, wherein the feature includes one or more of a characteristic, intensity, density, contrast, and shape of the region of the anatomical structure.
  • 29. The system of claim 1, wherein the imaging module and the therapy module are configured to function consecutively using an interleaving mechanism such that therapy is delivered substantially continuously.
  • 30. The system of claim 1, wherein the imaging module and the therapy module are configured to function concurrently using a continuous mechanism such that the target tissue may be tracked substantially continuously and the therapy may be delivered substantially continuously.
  • 31. The system of claim 1, wherein the therapy module is configured to predict a future location or a future feature of the target tissue and to deliver the therapy to the target tissue when the target tissue reaches the future location or the future feature.
  • 32. The system of claim 1, wherein the therapy module is configured to provide lithotripsy.
  • 33. The system of claim 32, wherein the lithotripsy comprises treatment of a kidney stone, gallstone, bile duct stone, or ureter stone.
  • 34. The system of claim 1, wherein the image is generated using ultrasound emitted from outside the patient.
  • 35. The system of claim 1, wherein the tracker compares a result to several previous images and uses a weighted function to obtain a final position.
  • 36. The system of claim 1, wherein the tracker first looks for changes near a previous location (In-1).
  • 37. The system of claim 1, wherein the detector detects a possible current location or feature of a region of anatomical structure on a current image (In) and compares a feature histogram of the possible current location or feature to the template pool comprising feature histograms for a plurality of template of previous locations and/or features of the region of the anatomical structure in previous images.
  • 38. The system of claim 1, wherein the system compensates automatically if a target becomes lost or unfocused.
  • 39. A system for tracking a renal artery during delivery of an ultrasound therapy to a patient, the system comprising: an imaging module configured to detect a possible current location and/or a feature of a region of an anatomical structure in an ultrasound image, wherein the imaging module comprises a tracker configured to compare the possible current location and/or feature to a template of one or more previous locations and/or features to generate a first input, a detector configured to compare the possible current location and/or feature to a template pool of previous locations and/or features to generate a second input, and an integrator, wherein the integrator is configured to obtain the first input from the tracker and the second input from the detector, and provide a positional data based at least in part on the first input from the tracker and/or the second input from the detector; anda therapy module comprising an ultrasound treatment transducer configured to deliver the ultrasound therapy to the renal artery and to adjust delivery of ultrasound based on the positional data, wherein the ultrasound treatment transducer is configured to be mechanically moved and/or electronically controlled.
  • 40. The system of claim 39, wherein the ultrasound treatment transducer comprises a full circular annular phased array.
  • 41. The system of claim 39, wherein the ultrasound treatment transducer comprises a partial circular annular phased array.
  • 42. The system of claim 39, wherein the ultrasound treatment transducer is configured to be directed and moved to guide therapeutic energy to the renal artery.
  • 43. The system of claim 39, wherein the ultrasound treatment transducer comprises a two-dimensional array and is configured to move therapy focus by a three-dimensional electronic control mechanism to guide therapeutic energy to the renal artery.
  • 44. The system of claim 39, wherein the ultrasound image is generated using ultrasound emitted from outside the patient.
CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to and the benefit of U.S. Provisional Patent Application No. 62/075,487, filed on Nov. 5, 2014, the entire disclosure of the above application is expressly incorporated by reference herein. This application is related to international PCT patent application serial No. PCT/US2014/022141, titled “TRANSDUCERS, SYSTEMS, AND MANUFACTURING TECHNIQUES FOR FOCUSED ULTRASOUND THERAPIES”, filed on Mar. 7, 2014, which is herein incorporated by reference in its entirety.

US Referenced Citations (513)
Number Name Date Kind
385256 Eggers Jun 1888 A
3274437 Mastrup Sep 1966 A
3499437 Balamuth May 1970 A
3552382 Mount Jan 1971 A
3599477 Cohen Aug 1971 A
3847016 Ziedonis Nov 1974 A
3927662 Ziedonis Dec 1975 A
3969578 Mezrich Jul 1976 A
4059098 Murdock Nov 1977 A
4167180 Kossoff Sep 1979 A
4197856 Northrop Apr 1980 A
4206763 Pendersen Jun 1980 A
4237901 Taenzer Dec 1980 A
4273127 Auth et al. Jun 1981 A
4469099 McEwen Sep 1984 A
4479494 McEwen Oct 1984 A
4484569 Driller et al. Nov 1984 A
4545386 Hetz et al. Oct 1985 A
4601296 Yerushalmi Jul 1986 A
4605010 McEwen Aug 1986 A
4688578 Takano et al. Aug 1987 A
4702732 Powers et al. Oct 1987 A
4708836 Gain et al. Nov 1987 A
4748985 Nagasaki Jun 1988 A
4757820 Itoh Jul 1988 A
4770175 McEwen Sep 1988 A
4773865 Baldwin Sep 1988 A
4773899 Spears Sep 1988 A
4784148 Dow et al. Nov 1988 A
4841979 Dow et al. Jun 1989 A
4850363 Yanagawa Jul 1989 A
4858613 Fry et al. Aug 1989 A
4905672 Schwarze et al. Mar 1990 A
4913155 Dow et al. Apr 1990 A
4929246 Sinofsky May 1990 A
4931047 Broadwin et al. Jun 1990 A
4938216 Lele Jul 1990 A
4938217 Lele Jul 1990 A
4957099 Hassler Sep 1990 A
4957481 Gatenby Sep 1990 A
5005579 Wurster et al. Apr 1991 A
RE33590 Dory May 1991 E
5026387 Thomas Jun 1991 A
5036855 Fry et al. Aug 1991 A
5039774 Shikinami et al. Aug 1991 A
5042486 Pfeiler et al. Aug 1991 A
5048527 Okazaki Sep 1991 A
5065742 Belikan et al. Nov 1991 A
5080101 Dory Jan 1992 A
5080102 Dory Jan 1992 A
5093570 Dorfi Mar 1992 A
5150712 Dory Sep 1992 A
5170790 Lacoste et al. Dec 1992 A
5178135 Uchiyama et al. Jan 1993 A
5178148 Lacoste et al. Jan 1993 A
5181522 McEwen Jan 1993 A
5193527 Schaefer Mar 1993 A
5194291 D'Aoust et al. Mar 1993 A
5211160 Talish et al. May 1993 A
5215680 D'Arrigo Jun 1993 A
5219401 Cathignol et al. Jun 1993 A
5230334 Klopotek Jul 1993 A
5230921 Waltonen et al. Jul 1993 A
5233994 Shmulewitz Aug 1993 A
5243988 Sieben et al. Sep 1993 A
5254087 McEwen Oct 1993 A
5263957 Davison Nov 1993 A
5290278 Anderson Mar 1994 A
5311869 Okazaki May 1994 A
5312431 McEwen May 1994 A
5352195 McEwen Oct 1994 A
5364389 Anderson Nov 1994 A
5383896 Gershony et al. Jan 1995 A
5391140 Schaetzle et al. Feb 1995 A
5391197 Burdette et al. Feb 1995 A
5394875 Lewis Mar 1995 A
5394877 Orr et al. Mar 1995 A
5413550 Castel May 1995 A
5415657 Taymor-Luria May 1995 A
5439477 McEwen Aug 1995 A
5445608 Chen et al. Aug 1995 A
5453576 Krivitski Sep 1995 A
5454373 Koger et al. Oct 1995 A
5454831 McEwen Oct 1995 A
5471988 Fujio et al. Dec 1995 A
5474071 Chapelon et al. Dec 1995 A
5479375 Gualtieri Dec 1995 A
5492126 Hennige et al. Feb 1996 A
5501655 Rolt et al. Mar 1996 A
5503152 Oakley et al. Apr 1996 A
5507744 Tay et al. Apr 1996 A
5507790 Weiss Apr 1996 A
5515853 Smith et al. May 1996 A
5520188 Hennige et al. May 1996 A
5522878 Montecalvo et al. Jun 1996 A
5524620 Rosenschein Jun 1996 A
5526815 Granz et al. Jun 1996 A
5534232 Denes et al. Jul 1996 A
5536489 Lohrmann et al. Jul 1996 A
5553618 Suzuki et al. Sep 1996 A
5556415 McEwen et al. Sep 1996 A
5558092 Unger et al. Sep 1996 A
5573497 Chapelon Nov 1996 A
5574212 Madsen Nov 1996 A
5578055 McEwen Nov 1996 A
5584853 McEwen Dec 1996 A
5598845 Chandraratna et al. Feb 1997 A
5601526 Chapelon et al. Feb 1997 A
5607447 McEwen et al. Mar 1997 A
5609485 Bergman et al. Mar 1997 A
5626601 Gershony et al. May 1997 A
5630837 Crowley May 1997 A
5638823 Akay et al. Jun 1997 A
5643179 Fujimoto Jul 1997 A
5649954 McEwen Jul 1997 A
5655538 Lorraine et al. Aug 1997 A
5657760 Ying et al. Aug 1997 A
5665073 Bulow et al. Sep 1997 A
5666954 Chapelon et al. Sep 1997 A
5681339 McEwen et al. Oct 1997 A
5685307 Holland et al. Nov 1997 A
5695493 Nakajima et al. Dec 1997 A
5697897 Buchholtz et al. Dec 1997 A
D389574 Emerson et al. Jan 1998 S
5711058 Frey et al. Jan 1998 A
5716374 Francese et al. Feb 1998 A
5720286 Chapelon et al. Feb 1998 A
5720287 Chapelon et al. Feb 1998 A
5722411 Suzuki Mar 1998 A
5726066 Choi Mar 1998 A
5735796 Granz et al. Apr 1998 A
5738635 Chapelon et al. Apr 1998 A
5741295 McEwen Apr 1998 A
5755228 Wilson et al. May 1998 A
5762066 Law et al. Jun 1998 A
5769790 Watkins et al. Jun 1998 A
5788636 Curley Aug 1998 A
5807285 Vaitekunas Sep 1998 A
5810007 Holupka et al. Sep 1998 A
5810810 Tay et al. Sep 1998 A
5817021 Reichenberger Oct 1998 A
5823962 Schaetzle et al. Oct 1998 A
5824015 Sawyer Oct 1998 A
5824277 Campos Oct 1998 A
5827204 Grandia et al. Oct 1998 A
5827268 Laufer Oct 1998 A
5833647 Edwards Nov 1998 A
5840028 Chubachi et al. Nov 1998 A
5846517 Unger Dec 1998 A
5852860 Lorraine et al. Dec 1998 A
5853752 Unger et al. Dec 1998 A
5855589 McEwen et al. Jan 1999 A
5873828 Fujio et al. Feb 1999 A
5873845 Cline et al. Feb 1999 A
5879314 Peterson et al. Mar 1999 A
5882302 Driscoll, Jr. et al. Mar 1999 A
5882328 Levy et al. Mar 1999 A
5895356 Andrus et al. Apr 1999 A
5904659 Duarte et al. May 1999 A
5906580 Kline-Schoder et al. May 1999 A
5911735 McEwen Jun 1999 A
5919139 Lin Jul 1999 A
5921994 Andreas et al. Jul 1999 A
5922945 Allmaras et al. Jul 1999 A
5931786 Whitmore, III et al. Aug 1999 A
5931853 McEwen Aug 1999 A
5935144 Estabrook Aug 1999 A
5935146 McEwen Aug 1999 A
5935339 Henderson et al. Aug 1999 A
5938600 Van Vaals et al. Aug 1999 A
5951476 Beach Sep 1999 A
5957849 Munro Sep 1999 A
5964782 Lafontaine et al. Oct 1999 A
5976092 Chinn Nov 1999 A
5979453 Savage et al. Nov 1999 A
5993389 Driscoll, Jr. et al. Nov 1999 A
5997481 Adams et al. Dec 1999 A
6007499 Martin et al. Dec 1999 A
6014473 Hossack et al. Jan 2000 A
6033506 Klett Mar 2000 A
6036650 Wu et al. Mar 2000 A
6037032 Klett et al. Mar 2000 A
6039694 Larson et al. Mar 2000 A
6050943 Slayton et al. Apr 2000 A
6067371 Gouge et al. May 2000 A
6068596 Weth et al. May 2000 A
6071239 Cribbs et al. Jun 2000 A
6071277 Farley et al. Jun 2000 A
6078831 Belef et al. Jun 2000 A
6083159 Driscoll, Jr. et al. Jul 2000 A
6087761 Lorraine et al. Jul 2000 A
6102860 Mooney Aug 2000 A
6106463 Wilk Aug 2000 A
6120453 Sharp Sep 2000 A
6128522 Acker et al. Oct 2000 A
6179831 Bliweis Jan 2001 B1
6182341 Talbot et al. Feb 2001 B1
6200539 Sherman et al. Mar 2001 B1
6206843 Iger et al. Mar 2001 B1
6213939 McEwen Apr 2001 B1
6217530 Martin et al. Apr 2001 B1
6221015 Yock Apr 2001 B1
6231507 Zikorus et al. May 2001 B1
6233477 Chia et al. May 2001 B1
6246156 Takeuchi et al. Jun 2001 B1
6254601 Burbank et al. Jul 2001 B1
6259945 Epstein et al. Jul 2001 B1
6263551 Lorraine et al. Jul 2001 B1
6267734 Ishibashi et al. Jul 2001 B1
6270458 Barnea Aug 2001 B1
6277077 Brisken et al. Aug 2001 B1
6315441 King Nov 2001 B2
6315724 Berman Nov 2001 B1
6332089 Acker et al. Dec 2001 B1
6361496 Zikorus et al. Mar 2002 B1
6361548 McEwen Mar 2002 B1
6399149 Klett et al. Jun 2002 B1
6406759 Roth Jun 2002 B1
6409720 Hissong et al. Jun 2002 B1
6419669 Frazier et al. Jul 2002 B1
6425867 Vaezy et al. Jul 2002 B1
6425876 Frangi et al. Jul 2002 B1
6432067 Martin et al. Aug 2002 B1
6443894 Sumanaweera et al. Sep 2002 B1
6453526 Lorraine et al. Sep 2002 B2
6488639 Ribault et al. Dec 2002 B1
6491672 Slepian et al. Dec 2002 B2
6494848 Sommercorn et al. Dec 2002 B1
6500133 Martin et al. Dec 2002 B2
6506171 Vitek et al. Jan 2003 B1
6514221 Hynynen et al. Feb 2003 B2
6520915 Lin et al. Feb 2003 B1
6522926 Kieval et al. Feb 2003 B1
6548047 Unger Apr 2003 B1
6551576 Unger et al. Apr 2003 B1
6559644 Froundlich et al. May 2003 B2
6562037 Paton et al. May 2003 B2
6565557 Sporri et al. May 2003 B1
6576168 Hardcastle et al. Jun 2003 B2
6584360 Francischelli et al. Jun 2003 B2
6593574 Thomas Jul 2003 B2
6595934 Hissong et al. Jul 2003 B1
6599256 Acker et al. Jul 2003 B1
6599288 Maguire Jul 2003 B2
6602251 Burbank et al. Aug 2003 B2
6612988 Maor et al. Sep 2003 B2
6616624 Kieval Sep 2003 B1
6626855 Weng et al. Sep 2003 B1
6633658 Dabney et al. Oct 2003 B1
6652461 Levkovitz Nov 2003 B1
6656131 Alster et al. Dec 2003 B2
6656136 Weng et al. Dec 2003 B1
6676601 Lacoste et al. Jan 2004 B1
6682483 Abend et al. Jan 2004 B1
6685639 Wang et al. Feb 2004 B1
6706892 Ezrin et al. Mar 2004 B1
6709392 Salgo et al. Mar 2004 B1
6709407 Fatemi Mar 2004 B2
6716184 Vaezy et al. Apr 2004 B2
6719694 Weng et al. Apr 2004 B2
6719699 Smith Apr 2004 B2
6726627 Lizzi et al. Apr 2004 B1
6728566 Subramanyan et al. Apr 2004 B1
6735461 Vitek et al. May 2004 B2
6755789 Stringer et al. Jun 2004 B2
6764488 Burbank et al. Jul 2004 B1
6846291 Smith et al. Jan 2005 B2
6875176 Mourad et al. Apr 2005 B2
6875420 Quay Apr 2005 B1
6905498 Hooven Jun 2005 B2
6932771 Whitmore et al. Aug 2005 B2
6955648 Mozayeni et al. Oct 2005 B2
6978174 Gelfand et al. Dec 2005 B2
7022077 Mourad et al. Apr 2006 B2
7052463 Peszynski et al. May 2006 B2
7063666 Weng et al. Jun 2006 B2
7128711 Medan et al. Oct 2006 B2
7149564 Vining et al. Dec 2006 B2
7162303 Levin et al. Jan 2007 B2
7211060 Talish et al. May 2007 B1
7260250 Summers et al. Aug 2007 B2
7285093 Anisimov et al. Oct 2007 B2
7374538 Nightingale et al. May 2008 B2
7445599 Kelly et al. Nov 2008 B2
7470241 Weng et al. Dec 2008 B2
7499748 Moffitt et al. Mar 2009 B2
7510536 Foley et al. Mar 2009 B2
7530958 Slayton et al. May 2009 B2
7534209 Abend May 2009 B2
7553284 Vaitekunas Jun 2009 B2
7617005 Demarais et al. Nov 2009 B2
7620451 Demarais et al. Nov 2009 B2
7628764 Duarte et al. Dec 2009 B2
7684865 Aldrich et al. Mar 2010 B2
7697972 Verard et al. Apr 2010 B2
7698947 Sarr Apr 2010 B2
7725184 Cazares May 2010 B2
7766833 Lee Aug 2010 B2
7783358 Aldrich et al. Aug 2010 B2
8295912 Gertner Oct 2012 B2
8347891 Demarais et al. Jan 2013 B2
8383671 Consigny Feb 2013 B1
8556834 Gertner Oct 2013 B2
8715209 Gertner May 2014 B2
9234878 Lavrentyev Jan 2016 B2
20010014775 Koger et al. Aug 2001 A1
20010014805 Burbank et al. Aug 2001 A1
20010032382 Lorraine et al. Oct 2001 A1
20010041910 McEwen Nov 2001 A1
20010044636 Pedros et al. Nov 2001 A1
20020055736 Horn et al. May 2002 A1
20020072672 Roundhill et al. Jun 2002 A1
20020095164 Andreas et al. Jul 2002 A1
20020143275 Sarvazyan Oct 2002 A1
20020193831 Smith, III Dec 2002 A1
20030009194 Saker et al. Jan 2003 A1
20030010124 Bates Jan 2003 A1
20030018255 Martin et al. Jan 2003 A1
20030036771 McEwen Feb 2003 A1
20030050665 Ginn Mar 2003 A1
20030060737 Brisken Mar 2003 A1
20030069569 Burdette et al. Apr 2003 A1
20030114756 Li Jun 2003 A1
20030120204 Unger et al. Jun 2003 A1
20030149366 Stringer et al. Aug 2003 A1
20030153849 Huckle et al. Aug 2003 A1
20030187371 Vortman et al. Oct 2003 A1
20030195420 Mendlein et al. Oct 2003 A1
20030208101 Cecchi Nov 2003 A1
20030216792 Levin et al. Nov 2003 A1
20030225331 Diederich et al. Dec 2003 A1
20040002654 Davidson et al. Jan 2004 A1
20040030227 Littrup et al. Feb 2004 A1
20040030268 Weng et al. Feb 2004 A1
20040030269 Horn et al. Feb 2004 A1
20040039280 Wu et al. Feb 2004 A1
20040049105 Crutchfield et al. Mar 2004 A1
20040054287 Stephens Mar 2004 A1
20040054289 Eberle et al. Mar 2004 A1
20040056200 Rothenfusser Mar 2004 A1
20040057492 Vona Mar 2004 A1
20040071664 McHale et al. Apr 2004 A1
20040078034 Acker et al. Apr 2004 A1
20040078219 Kaylor et al. Apr 2004 A1
20040082978 Harrison et al. Apr 2004 A1
20040089811 Lewis May 2004 A1
20040097805 Verard et al. May 2004 A1
20040097840 Holmer May 2004 A1
20040106880 Weng et al. Jun 2004 A1
20040113524 Baumgartner et al. Jun 2004 A1
20040122493 Ishibashi et al. Jun 2004 A1
20040127798 Dala-Krishna et al. Jul 2004 A1
20040153126 Okai Aug 2004 A1
20040158154 Hanafy et al. Aug 2004 A1
20040210214 Knowlton Oct 2004 A1
20040220167 Samly Nov 2004 A1
20040234453 Smith Nov 2004 A1
20040254620 Lacoste et al. Dec 2004 A1
20040267252 Washington et al. Dec 2004 A1
20050038339 Chauhan et al. Feb 2005 A1
20050038340 Vaezy et al. Feb 2005 A1
20050043625 Oliver et al. Feb 2005 A1
20050046311 Baumgartner et al. Mar 2005 A1
20050054955 Lidgren Mar 2005 A1
20050065436 Ho et al. Mar 2005 A1
20050070790 Niwa et al. Mar 2005 A1
20050085793 Glossop Apr 2005 A1
20050090104 Yang et al. Apr 2005 A1
20050092091 Greelish May 2005 A1
20050096538 Chomas et al. May 2005 A1
20050096542 Weng et al. May 2005 A1
20050119704 Peters et al. Jun 2005 A1
20050149126 Libbus Jul 2005 A1
20050154299 Hoctor et al. Jul 2005 A1
20050165298 Larson et al. Jul 2005 A1
20050182297 Gravenstein et al. Aug 2005 A1
20050182319 Glossop Aug 2005 A1
20050192638 Gelfand et al. Sep 2005 A1
20050240102 Rachlin et al. Oct 2005 A1
20050240103 Byrd et al. Oct 2005 A1
20050240126 Foley et al. Oct 2005 A1
20050240127 Seip et al. Oct 2005 A1
20050240170 Zhang et al. Oct 2005 A1
20050240241 Yun et al. Oct 2005 A1
20050261672 Deem et al. Nov 2005 A1
20050277853 Mast et al. Dec 2005 A1
20050288730 Deem et al. Dec 2005 A1
20060004417 Rossing Jan 2006 A1
20060025756 Francischelli et al. Feb 2006 A1
20060052701 Carter et al. Mar 2006 A1
20060058678 Vitek et al. Mar 2006 A1
20060058707 Barthe et al. Mar 2006 A1
20060082771 Doerrmann et al. Apr 2006 A1
20060084966 Maguire et al. Apr 2006 A1
20060122514 Byrd et al. Jun 2006 A1
20060184069 Vaitekunas Aug 2006 A1
20060235300 Weng et al. Oct 2006 A1
20060235303 Vaezy et al. Oct 2006 A1
20060287681 Yonce Dec 2006 A1
20060293712 Kieval et al. Dec 2006 A1
20070004984 Crum et al. Jan 2007 A1
20070016113 Buchholtz Jan 2007 A1
20070016274 Boveja et al. Jan 2007 A1
20070038115 Quigley et al. Feb 2007 A1
20070055155 Owen et al. Mar 2007 A1
20070055181 Deem et al. Mar 2007 A1
20070066957 Demarais et al. Mar 2007 A1
20070106339 Errico et al. May 2007 A1
20070112327 Yun et al. May 2007 A1
20070129720 Demarais et al. Jun 2007 A1
20070129761 Demarais et al. Jun 2007 A1
20070135875 Demarais et al. Jun 2007 A1
20070142879 Greenberg et al. Jun 2007 A1
20070149880 Willis Jun 2007 A1
20070167806 Wood et al. Jul 2007 A1
20070179379 Weng et al. Aug 2007 A1
20070203527 Ben-David et al. Aug 2007 A1
20070213616 Anderson et al. Sep 2007 A1
20070233185 Anderson et al. Oct 2007 A1
20070239000 Emery et al. Oct 2007 A1
20070265687 Deem et al. Nov 2007 A1
20070282407 Demarais et al. Dec 2007 A1
20080030104 Prus Feb 2008 A1
20080033292 Shafran Feb 2008 A1
20080033420 Nields et al. Feb 2008 A1
20080039746 Hissong et al. Feb 2008 A1
20080045864 Candy et al. Feb 2008 A1
20080045865 Kislev Feb 2008 A1
20080046016 Ben-David Feb 2008 A1
20080047325 Bartlett Feb 2008 A1
20080051767 Rossing et al. Feb 2008 A1
20080058683 Gifford et al. Mar 2008 A1
20080194954 Unger et al. Aug 2008 A1
20080200806 Liu et al. Aug 2008 A1
20080200815 Van Der Steen et al. Aug 2008 A1
20080234569 Tidhar et al. Sep 2008 A1
20080255498 Houle Oct 2008 A1
20080255642 Zarins et al. Oct 2008 A1
20080261009 Kawabata Oct 2008 A1
20080288017 Kieval Nov 2008 A1
20080312561 Chauhan Dec 2008 A1
20080312562 Routh et al. Dec 2008 A1
20080317204 Sumanaweera et al. Dec 2008 A1
20080319375 Hardy Dec 2008 A1
20090000382 Sathish Jan 2009 A1
20090012098 Jordan et al. Jan 2009 A1
20090036948 Levin et al. Feb 2009 A1
20090054770 Daigle Feb 2009 A1
20090062697 Zhang et al. Mar 2009 A1
20090062873 Wu et al. Mar 2009 A1
20090076409 Wu et al. Mar 2009 A1
20090088623 Vortman et al. Apr 2009 A1
20090099627 Molnar Apr 2009 A1
20090112095 Daigle Apr 2009 A1
20090112133 Deisseroth et al. Apr 2009 A1
20090137873 Mitsuhashi May 2009 A1
20090149782 Cohen et al. Jun 2009 A1
20090163982 Decharms Jun 2009 A1
20090221908 Glossop Sep 2009 A1
20090221939 Demarais et al. Sep 2009 A1
20090247911 Novak et al. Oct 2009 A1
20090264755 Chen et al. Oct 2009 A1
20090306644 Mayse et al. Dec 2009 A1
20090315978 Wurmlin Dec 2009 A1
20100010393 Duffy et al. Jan 2010 A1
20100022921 Seip et al. Jan 2010 A1
20100023088 Stack et al. Jan 2010 A1
20100042020 Ben-Ezra Feb 2010 A1
20100081971 Allison Apr 2010 A1
20100092424 Sanghvi et al. Apr 2010 A1
20100125269 Emmons et al. May 2010 A1
20100128141 Jang May 2010 A1
20100160781 Carter et al. Jun 2010 A1
20100174188 Wang et al. Jul 2010 A1
20100286522 Beach Nov 2010 A1
20110021913 Weng et al. Jan 2011 A1
20110028867 Choo et al. Feb 2011 A1
20110060255 Chen Mar 2011 A1
20110092781 Gertner Apr 2011 A1
20110092880 Gertner Apr 2011 A1
20110112400 Emery et al. May 2011 A1
20110118805 Wei May 2011 A1
20110124976 Sabczynski et al. May 2011 A1
20110234834 Sugimoto Sep 2011 A1
20110251489 Zhang et al. Oct 2011 A1
20110257523 Hastings Oct 2011 A1
20110257561 Gertner et al. Oct 2011 A1
20110260965 Kim Oct 2011 A1
20110319765 Gertner et al. Dec 2011 A1
20120065492 Gertner et al. Mar 2012 A1
20120109018 Gertner et al. May 2012 A1
20120123243 Hastings May 2012 A1
20130120552 Yamanaka May 2013 A1
20130245429 Zhang Sep 2013 A1
20140005477 Gupta Jan 2014 A1
20140043933 Belevich Feb 2014 A1
20140086684 Sehr Mar 2014 A1
20140171782 Bruder Jun 2014 A1
20140275705 Virshup Sep 2014 A1
20140316269 Zhang Oct 2014 A1
20140331771 Baba Nov 2014 A1
20150005613 Kim Jan 2015 A1
20150029819 Yacoubian Jan 2015 A1
20150092814 Wolfgruber Apr 2015 A1
20150175747 Liu Jun 2015 A1
20150231414 Ein-Gal Aug 2015 A1
20150253266 Lu con Sep 2015 A1
20160109393 Man Delis Apr 2016 A1
20160121142 Zhang May 2016 A1
20160299108 Bisle Oct 2016 A1
20160317122 dos Santos Mendonca Nov 2016 A1
20170097280 Drescher Apr 2017 A1
20170212066 Thompson Jul 2017 A1
Foreign Referenced Citations (24)
Number Date Country
0225120 Jun 1987 EP
0420758 Apr 1991 EP
0679371 Nov 1995 EP
1265223 Dec 2002 EP
1579889 Sep 2005 EP
1847294 Oct 2007 EP
H05-220152 Aug 1993 JP
2007000218 Jan 2007 JP
WO 9502361 Jan 1995 WO
WO 1997031364 Aug 1997 WO
WO 1999048621 Sep 1999 WO
WO 2001034018 May 2001 WO
WO 2002069805 Sep 2002 WO
WO 2005030295 Apr 2005 WO
WO 2006003606 Jan 2006 WO
WO 2006121447 Nov 2006 WO
WO 2006129099 Dec 2006 WO
WO 2008144274 Nov 2008 WO
WO 2009003138 Dec 2008 WO
WO 2009018351 Feb 2009 WO
WO 2009018394 Feb 2009 WO
WO 2009081339 Jul 2009 WO
WO 2011053757 May 2011 WO
WO 2011053772 May 2011 WO
Related Publications (1)
Number Date Country
20160121142 A1 May 2016 US
Provisional Applications (1)
Number Date Country
62075487 Nov 2014 US