Patent Application
20100189324
The invention relates generally to imaging systems, and more particularly, embodiments relate to an apparatus and method for reducing image artifacts that are produced by movement of an object.
Multi-modality imaging systems exist that scan using different modalities, such as, for example, Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), and Single Photon Emission Computed Tomography (SPECT). During operation, conventional imaging systems may exhibit image quality that is affected by motion of the object being imaged.
Motion of the object being imaged may degrade image quality, for example in medical imaging. More specifically, image artifacts are produced by movement of the object. Respiratory motion is a common source of involuntary motion in mammals (e.g., people and animals) encountered in medical imaging systems. The respiratory motion may lead to errors, such as when a physician is determining the size of a lesion, determining the location of the lesion, or quantifying the lesion.
To correct for motion related imaging artifacts, at least one conventional imaging system utilizes respiratory information. In cases where the data acquisition period is relatively long, conventional imaging systems monitor the patients' breathing using a respiration monitor. The signal generated by the respiration monitor is then used to reduce artifacts in the acquired image data. The conventional motion correction method relies on the assumption that the movement of internal structures in a region of interest is the same over different breathing cycles. However, involuntary motion during respiration may cause a hysteresis effect to occur.
Conventional imaging systems ignore the hysteresis effect resulting in increased motion related artifacts. The hysteresis effect occurs when the movement path followed by the internal structure during inspiration does not coincide with the path followed by the internal structure during expiration. Also, in some cases, the movement of the internal structure may lag behind the respiration signal. For example, deep breathing may cause the internal structure to be at a different position than when shallow breathing is performed. Moreover, if the object breathes faster or slower, the movement of some internal structures may exhibit a delay in reacting to the changes in direction of diaphragm movement.
In one embodiment, a method for reducing, in an images motion related imaging artifacts is provided. The method includes obtaining an image data set of a region of interest in an object, obtaining a motion signal indicative of motion of the region of interest, and determining a displacement and a phase of at least a portion of the motion signal. The method also includes mapping the image data set into a matrix based on the displacement and phase of the motion signal, and generating an image of the region of interest from the matrix.
In another embodiment, a multi-modality imaging system is provided. The multi-modality imaging system includes a first modality unit, a second modality unit, and a computer operationally coupled to the first and second modality units. The computer is programmed to obtain an image data set of a region of interest in an object, obtain a motion signal indicative of motion of the region of interest, determine a displacement and a phase of at least a portion of the motion signal, gate the image data set into a matrix based on the displacement and phase of the motion signal, and generate an image of the region of interest from the matrix.
In a further embodiment, a computer readable medium is provided. The computer readable medium is programmed to instruct a computer to obtain an image data set of a region of interest in an object, obtain a motion signal indicative of motion of the region of interest, determine a displacement and a phase of at least a portion of the motion signal, gate the image data set into a matrix based on the displacement and phase of the motion signal, and generate an image of the region of interest from the matrix.
The foregoing summary, as well as the following detailed description of certain embodiments of the present invention, will be better understood when read in conjunction with the appended drawings. To the extent that the figures illustrate diagrams of the functional blocks of various embodiments, the functional blocks are not necessarily indicative of the division between hardware circuitry. Thus, for example, one or more of the functional blocks (e.g., processors or memories) may be implemented in a single piece of hardware (e.g., a general purpose signal processor or a block of random access memory, hard disk, or the like). Similarly, the programs may be stand alone programs, may be incorporated as subroutines in an operating system, may be functions in an installed software package, and the like. It should be understood that the various embodiments are not limited to the arrangements and instrumentality shown in the drawings.
As used herein, an element or step recited in the singular and proceeded with the word “a” or “an” should be understood as not excluding plural of said elements or steps, unless such exclusion is explicitly stated. Furthermore, references to “one embodiment” of the present invention are not intended to be interpreted as excluding the existence of additional embodiments that also incorporate the recited features. Moreover, unless explicitly stated to the contrary, embodiments “comprising” or “having” an element or a plurality of elements having a particular property may include additional elements not having that property.
Also as used herein, the phrase “reconstructing an image” is not intended to exclude embodiments of the present invention in which data representing an image is generated but a viewable image is not. Therefore, as used herein the term “image” broadly refers to both viewable images and data representing a viewable image. However, many embodiments generate, or are configured to generate, at least one viewable image.
Various embodiments of the invention provide a multi-modality imaging system 10 as shown in
Referring to
The gantry 18 includes an x-ray source 26 that projects a beam of x-rays toward a detector array 28 on the opposite side of the gantry 18. Detector array 28 is formed by a plurality of detector rows (not shown) including a plurality of detector elements which together sense the projected x-rays that pass through the object 16. Each detector element produces an electrical signal that represents the intensity of an impinging x-ray beam and hence allows estimation of the attenuation of the beam as it passes through the object 16. During a scan to acquire x-ray projection data, gantry 18 and the components mounted thereon rotate about a center of rotation.
The imaging system 10 also includes at least one motion sensor 29 that is adapted to detect and transmit information that is indicative of the motion of the object 16. In one embodiment, the motion sensor 29 may be a belt-type motion sensor 31 that is adapted to extend at least partially around the object 16. Optionally, the motion sensor 29 may be a motion sensor 33 that is adapted to be secured to a predetermined position on the object 16. It should be realized that although two different motion sensors or detectors are illustrated, that the imaging system may include other types of motions sensors to generate motion related information.
The detector ring assembly 30 includes the central opening 22, in which an object or patient, such as object 16 may be positioned, using, for example, the motorized table 24 (shown in
The workstation 34 may be embodied as a personal computer (PC) that is positioned near the PET imaging system 14 and hard-wired to the PET scanner controller 36 via the communication link 38. The workstation 34 may also be embodied as a portable computer such as a laptop computer or a hand-held computer that transmits information to the PET scanner controller 36. In one embodiment, the communication link 38 may be hardwired between the PET scanner controller 36 and the workstation 34. Optionally, the communication link 38 may be a wireless communication link that enables information to be transmitted to or from the workstation to the PET scanner controller 36 wirelessly. In the exemplary embodiment, the workstation 34 controls real-time operation of the PET imaging system 14. The workstation 34 is also programmed to perform medical image diagnostic acquisition and reconstruction processes described herein.
The operator workstation 34 includes a central processing unit (CPU) or computer 40, a display 42 and an input device 44. As used herein, the term “computer” may include any processor-based or microprocessor-based system including systems using microcontrollers, reduced instruction set computers (RISC), application specific integrated circuits (ASICs), field programmable gate array (FPGAs), logic circuits, and any other circuit or processor capable of executing the functions described herein. The above examples are exemplary only, and are thus not intended to limit in any way the definition and/or meaning of the term “computer”. In the exemplary embodiment, the computer 40 executes a set of instructions that are stored in one or more storage elements or memories, in order to process input data. The storage elements may also store data or other information as desired or needed. The storage element may be in the form of an information source or a physical memory element within the computer 40.
The set of instructions may include various commands that instruct the computer or processor 40 as a processing machine to perform specific operations such as the methods and processes of the various embodiments described herein. The set of instructions may be in the form of a software program. As used herein, the terms “software” and “firmware” are interchangeable, and include any computer program stored in memory for execution by a computer, including RAM memory, ROM memory, EPROM memory, EEPROM memory, and non-volatile RAM (NVRAM) memory. The above memory types are exemplary only, and are thus not limiting as to the types of memory usable for storage of a computer program.
The software may be in various forms such as system software or application software. Further, the software may be in the form of a collection of separate programs, a program module within a larger program or a portion of a program module. The software also may include modular programming in the form of object-oriented programming. The processing of input data by the processing machine may be in response to user commands, or in response to results of previous processing, or in response to a request made by another processing machine.
The CPU 40 connects to the communication link 38 and receives inputs, e.g., user commands, from the input device 44. The input device 44 may be, for example, a keyboard, mouse, a touch-screen panel, and/or a voice recognition system, etc. Through input device 44 and associated control panel switches, the operator can control the operation of the PET imaging system 14 and the positioning of the object 16 for a scan. Similarly, the operator can control the display of the resulting image on the display 42 and can perform image-enhancement functions using programs executed by the workstation CPU 40.
During operation of one exemplary detector, when a photon collides with a scintillator on the detector ring assembly 30, the photon collision produces a scintilla on the scintillator. The scintillator produces an analog signal that is transmitted on a communication link 46 when a scintillation event occurs. A set of acquisition circuits 48 is provided to receive these analog signals. The acquisition circuits 48 produce digital signals indicating the 3-dimensional (3D) location and total energy of each event. The acquisition circuits 48 also produce an event detection pulse, which indicates the time or moment the scintillation event occurred.
The digital signals are transmitted through a communication link, for example, a cable, to a data acquisition controller 52. The data acquisition controller 52 is adapted to perform the motion characterization and image reconstruction processes as described herein and various other functions. In one embodiment, the controller 52 is positioned remotely from the workstation 34 and communicates with the workstation 34 and PET scanner controller 36 via a communication link 54. Optionally, the controller 52 may be embedded within the workstation 34. For example, the controller 52 may be physically separate from the CPU 40 and used in conjunction with the CPU 40 to improve or enhance the image processing speed. In another embodiment, the CPU 40 may perform all the processing functions performed by the controller 52, e.g. the controller 52 is embedded in the workstation 34 such that CPU 40 performs the normalization and image reconstruction processes performed by the controller 52.
In one embodiment, the data acquisition controller 52 includes a data acquisition processor 60 and an image reconstruction processor 62 that are interconnected via a communication link 64. During operation, the acquisition circuits 48 transmit the digital signals to the data acquisition processor 60. The data acquisition processor 60 then performs various image enhancing techniques on the digital signals and transmits the enhanced or corrected digital signals to the image reconstruction processor 62 as discussed in more detail below.
In the exemplary embodiment, the data acquisition processor 60 includes at least an acquisition CPU or computer 70. The data acquisition processor 60 also includes an event locator circuit 72 and a coincidence detector 74. The acquisition CPU 70 controls communications on a back-plane bus 76 and on the communication link 64. During operation, the data acquisition processor 60 periodically samples the digital signals produced by the acquisition circuits 48. The digital signals produced by the acquisition circuits 48 are transmitted to the event locator circuit 72. The event locator circuit 72 processes the information to identify each valid event and provide a set of digital numbers or values indicative of the identified event. For example, this information indicates when the event took place and the position of the scintillator that detected the event. The events are also counted to form a record of the single channel events recorded by each detector element. An event data packet is communicated to the coincidence detector 74 through the back-plane bus 76.
The coincidence detector 74 receives the event data packets from the event locator circuit 72 and determines if any two of the detected events are in coincidence. Coincidence is determined by a number of factors. First, the time markers in each event data packet must be within a predetermined time period, for example, 12.5 nanoseconds, of each other. Second, the line-of-response (LOR) formed by a straight line joining the two detectors that detect the coincidence event should pass through the field of view in the PET imaging system 14. Events that cannot be paired are discarded. Coincident event pairs are located and recorded as a coincidence data packets by the coincidence detector 74 and are communicated through the back-plane bus 76 to a motion characterization module 78. The output from the coincidence detector 74 is referred to herein as an emission data set 80 or raw image data. In one embodiment, the emission data set 80 may be stored in a memory 82 that is located in the data acquisition processor 60. Optionally, the emission data set 80 may be stored in the workstation 34. As shown in
At 102, an image data set of a region of interest 17 of the object 16 (each shown in
At 104 a signal indicative of motion of the region of interest 17 of object 16 is obtained. For example,
Referring again to
Referring again to
Referring again to
A
g(t)<A(t)<Ag+1(t) (Eqn. 1)
where Ag(t) and Ag+1(t) define the displacement boundaries of each cell 136 to which the emission data is assigned based on the displacement of the motion signal 112; and A(t) is the motion signal 112 over time. The displacement boundaries defined by Ag may vary with respect to time. For example, the displacement boundaries may vary among multiple cycles 114.
At operation 108, the phase, e.g. phase 121 and/or phase 122 of the motion signal 112 is determined. More specifically, the phase or direction of the motion signal 112, e.g. increasing or decreasing, inspiration or expiration is determined in accordance with:
s=sign(Ã(t)−Ã(t−Δ)) (Eqn. 2)
where s denotes the direction of the motion signal 112; (Ã(t)) denotes the (optionally processed) motion signal 112 at a given time; and Δ denotes a time constant that is preselected based on the expected hysteresis; for example Δ≅200 milliseconds. In one embodiment, A may be smaller than an expected period of the phase of the motion signal 112. Δ may be significantly smaller than the phase period, but not so small that Δ would be sensitive to noise. By way of example only, Δ may be less than one tenth of the phase period of the motion signal 112. In one embodiment, the motion signal is processed using a denoising filter. For example, (Ã(t)) would be computed by a running average of the original signal (A(t)). While only two phases 121, 122 are referred to in the example above and shown in
d=(Ã(t)−Ã(t−Δ))
As shown in
At 109 the emission data set 80 is mapped into the matrix 130 based on the determined discretized displacement g and phase s of the signal 112 using a matrix populating or building module 85 shown in
For example, referring again to
Referring again to
Referring back to
In the exemplary embodiment, the motion signal 112 includes three cycles 114, wherein each cycle 114 has an inspiration and expiration phase. Accordingly, in the exemplary embodiment, the matrix 130 includes six columns 134, wherein each column is adapted to receive emission data related to a specific phase, either inspiration or expiration, of a single cycle 114. For example, the first column 150 includes the emission data that was collected during an expiration phase 154 of a first exemplary breathing cycle 156 and the second column includes the emission data 80 acquired during an inspiration phase of the respiratory cycle.
Additionally, the quantity of rows 132 is based on a quantity of ranges that the displacement of the motion signal 112 is divided. More specifically, the motion signal 112 may be divided into any quantity of ranges based on the displacement of the motion signal. In the exemplary embodiment, the displacement of the motion signal 112 is divided into three displacement ranges 159, 161, and 163, for example. Referring to
The matrix populating module 85 utilizes the displacement values and phases determined by the motion signal analysis module 84 to populate both the matrix 130 and matrix 170 with emission data 80. For example, the matrix populating module 85 utilizes mathematical language to gate the emission data located at a predetermined time to a cell (g, s) based on both the displacement and phase of the motion signal 112 at the given time. The cell (g, s) and the cycle number are each used to construct the matrix.
Referring again to
After the cells are identified at operation 115, the cells including emission data are combined at 116 into at least one bin. In one embodiment, cells having the same phase and the same range of displacement values are identified and combined into a single bin. For example,
For example, referring again to
In another embodiment, the decision as to which bin 200-205 an event belongs may be made on the basis of information acquired using the respiratory sensor 60 or on another motion signal. For example, if it is determined that motion is substantially periodic, the number of bins may be reduced, e.g. the displacement range could even be ignored when combining cells. As another example, at least some of the matrix cells may be designated “abnormal” and therefore rejected or combined into a “low-resolution” bin. For example, a cycle could be designated as irregular, and cells during this cycle as “abnormal”. As another example, this designation could be made on the basis of the displacement and phase range of the cell. This relies on the fact that data acquired during “regular” cycles will fill only part of the matrix. Examples of “abnormal” data in the case of respiratory movement include very deep breaths which will have larger displacements than average (during part of the cycle); and very shallow breaths which will have smaller displacements than average (usually during inspiration and expiration, but not during the resting phase at the end of expiration, so it might be advantageous to use more than 2 phase ranges for this example). Abnormality of a displacement and phase range could be determined on the basis of its duration, i.e. the amount of time during which the motion signal occurred in the corresponding cells. For example, if the duration of a particular displacement and phase range is substantially lower than for other ranges, the information in the corresponding matrix cells may be designated “abnormal” , and hence rejected or combined into a “low-resolution” bin. Optionally, abnormality may also be decided from a training set of curves (e.g. acquired with the motion tracker before acquisition) or from another (supposedly matching) data-set. Data from two subsequent acquisitions which have been classified as belonging to cells in the matrix corresponding to the same displacement and phase range can have matching locations of the organs. Therefore, cells corresponding to a displacement and phase range for which no signal occurred during one of the acquisitions could be rejected (or combined). One example includes matching CT and PET data. From the above examples, it should be clear that cells belonging to different displacement and phase ranges can potentially be combined into the same bin. In another exemplary embodiment, A method the cells having a different pre-determined displacement ranges and pre-determined signal phase ranges may be combined into a single low-resolution bin based on a second motion signal.
Referring again to
Referring again to
The image reconstruction processor 62 also includes a memory module 212, an image CPU 214, an array processor 216, and a communication bus 218. During operation, the sorter/histogrammer 210 counts all events in the bins of the histogram as discussed above. This data is organized in one exemplary embodiment as a data array 220. The data array 220 is stored in the memory module 212. The communication bus 218 is linked to the communication link 76 through the image CPU 214. The image CPU 214 controls communication through communication bus 218. The array processor 216 is also connected to the communication bus 218. The array processor 216 receives the data array 220 as an input and reconstructs images in the form of image arrays 222. Resulting image arrays 222 are then stored in memory module 212. The images stored in the image array 222 are communicated by the image CPU 214 to the operator workstation 34.
A technical effect of method 100 is to provide a fully automatic method of characterizing and reducing imaging artifacts caused by hysteresis in either transmission or emission data. Specifically, a matrix of cells is generated. Each cell in the matrix includes emission data having both a displacement value and a phase value. Similar cells, e.g. cells having both a common phase value, and falling within a common range of displacement values, may then be combined into a single bin. The bins may then be used to generate an image of the object. Moreover, since each bin includes similar displacement and phase values, the effects of hysteresis is either reduced and/or eliminated. As a result, the image(s) generated using the bins has(have) less artifacts than known imaging methods.
Moreover, the method and apparatus described herein combine the features of both displacement and phase-based gating to keep the advantages of displacement-based gating, but take some of the hysteresis effect into account. The method describes the use of two or more sets of gates, e.g. one set of gates for inspiration and one set of gates for expiration. During completely regular breathing, the method described herein includes the same advantages as phase-based gating and also works well for very elastic tissue. During irregular breathing, the method described herein takes the displacement of the breathing into account. In particular, the method described herein results in better motion-freezing than either displacement or phase-based gating. The method described herein is useful during medical imaging, and in other cases where the location of the internal structures need to be known, and in particular for radiotherapy. The method described herein may also be used outside of medical imaging wherein the motion is mainly correlated by the displacement of a certain signal, but some hysteresis is observed.
The methods and apparatus described herein provide a fully automatic method of characterizing and reducing imaging artifacts caused by hysteresis in either transmission or emission data. A technical effect of the above describes methods is to increase the accuracy of identifying the location of lesions and other features desired to be observed by the operator.
Some embodiments of the present invention provide a machine-readable medium or media having instructions recorded thereon for a processor or computer to operate an imaging apparatus to perform an embodiment of a method described herein. The medium or media may be any type of CD-ROM, DVD, floppy disk, hard disk, optical disk, flash RAM drive, or other type of computer-readable medium or a combination thereof.
The various embodiments and/or components, for example, the monitor or display, or components and controllers therein, also may be implemented as part of one or more computers or processors. The computer or processor may include a computing device, an input device, a display unit and an interface, for example, for accessing the Internet. The computer or processor may include a microprocessor. The microprocessor may be connected to a communication bus. The computer or processor may also include a memory. The memory may include Random Access Memory (RAM) and Read Only Memory (ROM). The computer or processor further may include a storage device, which may be a hard disk drive or a removable storage drive such as a floppy disk drive, optical disk drive, and the like. The storage device may also be other similar means for loading computer programs or other instructions into the computer or processor.
It is to be understood that the above description is intended to be illustrative, and not restrictive. For example, the above-described embodiments (and/or aspects thereof) may be used in combination with each other. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from its scope. For example, the ordering of steps recited in a method need not be performed in a particular order unless explicitly stated or implicitly required (e.g., one step requires the results or a product of a previous step to be available). While the dimensions and types of materials described herein are intended to define the parameters of the invention, they are by no means limiting and are exemplary embodiments. Many other embodiments will be apparent to those of skill in the art upon reviewing and understanding the above description. The scope of the invention should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled. In the appended claims, the terms “including” and “in which” are used as the plain-English equivalents of the respective terms “comprising” and “wherein.” Moreover, in the following claims, the terms “first,” “second,” and “third,” etc. are used merely as labels, and are not intended to impose numerical requirements on their objects. Further, the limitations of the following claims are not written in means-plus-function format and are not intended to be interpreted based on 35 U.S.C. §112, sixth paragraph, unless and until such claim limitations expressly use the phrase “means for” followed by a statement of function void of further structure.
This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the invention is defined by the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements with insubstantial differences from the literal languages of the claims.
