The evolution of medical imaging systems has progressively moved away from simple anatomic imaging towards functional imaging, which can detect and even quantify changes in various tissue properties, including metabolism, blood flow, and absorption. For example, functional imaging typically employs imaging modalities that utilize tracers or contrast agents to detect physiological activities of tissues and organs over a time and with multiple successive images.
Recent advances have yielded new techniques, such as arterial spin labeling (ASL), that no longer require these extrinsic agents, albeit at the cost of lower signal-to-noise. Regardless of the imaging modality or technique employed in functional imaging, reliable measurements of tissue properties can require successive images at the same anatomic location. This can make them susceptible to error resulting from image misalignment due to patient movement, respiratory/cardiac motion, and other sources of physiologic motion.
Image processing techniques according to the present disclosure can provide for the alignment of unregistered image data of multiple images of the same object, region, or location. The techniques can increase the signal-to-noise ratio (SNR) of the images.
An aspect of the present disclosure is directed to a general image processing method that includes segmenting boundaries of a region of interest (ROI) and identifying one or more control points, in each of multiple images of the same object, region, or location. The coordinates of each image are transformed from image coordinates into a coordinate frame relative to the control point or points. Image data is resampled and filtered and/or averaged. One or more material properties can be calculated from the resampled and filtered image data and then displayed.
A further aspect of the present disclosure is directed to an imaging and display system to implement methods according to the present disclosure. An imaging system provides unregistered imaging data to a memory unit and processor. The memory unit and/or processor may be connected to a display.
Exemplary embodiments are directed to medical imaging and may utilize any type of medical imaging modalities.
These, as well as other components, steps, features, benefits, and advantages of the present disclosure, will now become clear from a review of the following detailed description of illustrative embodiments, the accompanying drawings, and the claims.
The drawing figures depict one or more implementations in accord with the present teachings, by way of example only, not by way of limitation. They do not set forth all embodiments. Other embodiments may be used in addition or instead. Details that may be apparent or unnecessary may be omitted to save space or for more effective illustration. Conversely, some embodiments may be practiced without all of the details that are disclosed. When the same numeral appears in different drawings, it refers to the same or like components or steps. The drawings are not necessarily to scale, emphasis instead being placed on the principles of the disclosure. In the drawings:
While certain embodiments are depicted in the drawings, one skilled in the art will appreciate that the embodiments depicted are illustrative and that variations of those shown, as well as other embodiments described herein, may be envisioned and practiced within the scope of the present disclosure.
In the following detailed description, numerous specific details are set forth by way of examples in order to provide a thorough understanding of the relevant teachings. However, it should be apparent to those skilled in the art that the present teachings may be practiced without such details. In other instances, well known methods, procedures, components, and/or circuitry have been described at a relatively high-level, without detail, in order to avoid unnecessarily obscuring aspects of the present teachings.
Aspects of the present disclosure provide simple and effective methods that align unregistered image data and boost the signal-to-noise ratio (SNR) of low SNR imaging techniques, such as functional imaging or other types of imaging. After performing quantitative analysis of the desired property (e.g., a tissue property or property of other type of material) on the aligned images, the data can be mapped and displayed in a form that can be easily interpreted.
As is described below, exemplary embodiments are directed to medical imaging such as functional imaging of the heart. The scope of the present disclosure is not limited to medical imaging, however, and other imaging techniques may be utilized and non-medical subjects may be imaged.
An example of step 102 as applied to myocardial ASL is shown in
Returning to
An example of step 104 as applied to myocardial ASL, such as shown in
Further for method 100, image data is resampled and filtered and/or averaged, as described at 106. Image data may become irregularly spaced in the new coordinate frame, e.g., arising from a transformation from rectangular to polar coordinates. It is desirable therefore to resample such data in order to facilitate analysis and display. Each resampled data point can be computed as a weighted average of pixel intensities within a user defined (or, automatically defined) spatio-temporal window that is centered about that point. Many filters can be chosen. Exemplary filters include, but are not limited to, those that follow a standard window such as the Gaussian, Hamming, Hanning, Kaiser-Bessel, etc. In many embodiments, data points further from the center of the window will have a smaller contribution than more central data points.
An example of the resampling and filtering of step 106 as applied to myocardial ASL is shown in
Continuing with the description of method 100 of
An example of step 108, e.g., as derived from an image of the left ventricle such as shown in
In myocardial perfusion imaging, MBF data is displayed on an annular ring to match the corresponding slice—basal, mid, or apical—of the standard left ventricular segmentation model. The 17-segment model of the left ventricle has been adopted by the American Heart Association to provide a standard for clinicians to assess and interpret myocardial perfusion, left ventricular function, and coronary anatomy from tomographic images of the heart.
An exemplary embodiment can be implemented for myocardial perfusion imaging, as shown in
As shown in
The processor 606 may include or run suitable software (programming, or computer-readable instructions resident in a computer-readable storage medium) for image processing. Examples of suitable imaging software include but are not limited to MATLAB, e.g., MATLAB Release 2011b, as made commercially available by the MathWorks, and Interactive Data Language (IDL), e.g., IDL version 8, as made commercially available by ITT Visual Information System. Such software, when appropriately modified or programmed to carry out techniques such as shown and described for
Accordingly, the techniques as described herein can offer advantages and improvements over other methods of addressing image misregistration.
For example, image misalignment caused by patient movement and other sources of physiologic motion is a common problem in time-series data. Techniques, such as described for
Techniques as described herein can also provide for increased SNR. In low SNR imaging techniques, noise is often a problem that can corrupt the quality of data. High noise limits both the sensitivity and specificity of functional imaging to detect disease and pathology. Therefore, noise reduction is critical for clinical application. A common method to increase SNR is through temporal signal averaging of many image samples. A large number of samples, however, can be impractical in imaging techniques with long image acquisition times and degrades temporal resolution. Techniques of the present disclosure can increase SNR through both spatial and temporal signal averaging, giving the user more flexibility in choosing a balance between temporal and spatial resolution.
Exemplary embodiments can provide for transmural heterogeniety of the left ventricular wall. Irreversible ischemic injury to the myocardium is described as a transmural wavefront, beginning in the subendocardium. As the duration of ischemia increases, this wavefront of necrosis spreads to involve more of the transmural thickness of the left ventricle, eventually involving the entire transmural thickness. Most myocardial perfusion scans, however, are unable to analyze MBF by myocardial layer. By providing the ability to assess MBF by myocardial layers, techniques of the present disclosure may afford or facilitate the early detection of ischemic injury.
The techniques of the present disclosure are general enough such that they can be implemented using any medical imaging modality, including, but not limited to MRI, CT, X-ray, and ultrasound, as well as imaging techniques utilizing visible light, infrared light, and/or ultraviolet light, e.g., spectroscopic techniques. Consequently, this invention can be used to analyze and quantify functional imaging data of any tissue property at any anatomic location that medical imaging can perform. This includes imaging blood flow, oxygenation, glucose, metabolism, chemical composition, absorption, and any other physiological activity that can be functionally imaged.
In addition to application to medical imaging, the techniques of the present disclosure are general enough such that they can be implemented using other imaging modalities and for non-medical imaging as well. For example, techniques of the present disclosure may be used with MRI, CT, X-ray, and ultrasound imaging used on non-living matter, such as luggage, cargo containers, etc.
As described previously, techniques of the present disclosure may utilize signal averaging and filtering in order to improve the SNR of low SNR imaging techniques. The specific choice of filter is not limited and the user may decide which filter best suits his or her needs (or that choice may be made for the user). The choice of window size, shape, and dimension to perform signal averaging and filtering is also arbitrary and up to the user (or those choices made for the user). For example, embodiments can be implemented in three dimensions with a window that designates a volume of interest and a filter defined along all three physical axes.
Accordingly, techniques of the present disclosure provide for alignment of unregistered image data, an increase of the SNR of low SNR imaging techniques, and the display of imaging (e.g., functional medical imaging) data that facilitates interpretation (e.g., clinical interpretation). Exemplary embodiments have been applied to myocardial perfusion imaging using ASL MRI and may be used to successfully detect single vessel disease.
Aspects of the methods of image processing outlined above may be embodied in programming. Program aspects of the technology may be thought of as “products” or “articles of manufacture” typically in the form of executable code and/or associated data that is carried on or embodied in a type of non-transitory machine readable medium. “Storage” type media include any or all of the tangible memory of the computers, processors or the like, or associated modules thereof, such as various semiconductor memories, tape drives, disk drives and the like, which may provide non-transitory storage at any time for the software programming. All or portions of the software may at times be communicated through the Internet or various other telecommunication networks. Such communications, for example, may enable loading of the software from one computer, processor, or device into another, for example, from a management server or host computer of the service provider into the computer platform of the application server that will perform the function of the push server. Thus, another type of media that may bear the software elements includes optical, electrical and electromagnetic waves, such as used across physical interfaces between local devices, through wired and optical landline networks and over various air-links. The physical elements that carry such waves, such as wired or wireless links, optical links or the like, also may be considered as media bearing the software. As used herein, unless restricted to non-transitory, tangible “storage” media, terms such as computer or machine “readable medium” refer to any medium that participates in providing instructions to a processor for execution.
Hence, a machine readable medium may take many forms, including but not limited to, a tangible storage medium, a carrier wave medium or physical transmission medium. Non-volatile storage media include, for example, optical or magnetic disks, such as any of the storage devices in any computer(s), server(s), or the like, such as may be used to implement the push data service shown in the drawings. Volatile storage media include dynamic memory, such as main memory of such a computer platform. Tangible transmission media include coaxial cables; copper wire and fiber optics, including the wires that comprise a bus within a computer system. Carrier-wave transmission media can take the form of electric or electromagnetic signals, or acoustic or light waves such as those generated during radio frequency (RF) and infrared (IR) data communications. Common forms of computer-readable media therefore include for example: a floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM, DVD or DVD-ROM, any other optical medium, punch cards paper tape, any other physical storage medium with patterns of holes, a RAM, a PROM and EPROM, a FLASH-EPROM, any other memory chip or cartridge, a carrier wave transporting data or instructions, cables or links transporting such a carrier wave, or any other medium from which a computer can read programming code and/or data. Many of these forms of computer readable media may be involved in carrying one or more sequences of one or more instructions to a processor for execution.
While the foregoing has described what are considered to be the best mode and/or other examples, it is understood that various modifications may be made therein and that the subject matter disclosed herein may be implemented in various forms and examples, and that the teachings may be applied in numerous applications, only some of which have been described herein. It is intended by the following claims to claim any and all applications, modifications and variations that fall within the true scope of the present teachings.
Unless otherwise stated, all measurements, values, ratings, positions, magnitudes, sizes, and other specifications that are set forth in this specification, including in the claims that follow, are approximate, not exact. They are intended to have a reasonable range that is consistent with the functions to which they relate and with what is customary in the art to which they pertain.
The scope of protection is limited solely by the claims that now follow. That scope is intended and should be interpreted to be as broad as is consistent with the ordinary meaning of the language that is used in the claims when interpreted in light of this specification and the prosecution history that follows and to encompass all structural and functional equivalents. Notwithstanding, none of the claims are intended to embrace subject matter that fails to satisfy the requirement of Sections 101, 102, or 103 of the Patent Act, nor should they be interpreted in such a way. Any unintended embracement of such subject matter is hereby disclaimed.
Except as stated immediately above, nothing that has been stated or illustrated is intended or should be interpreted to cause a dedication of any component, step, feature, object, benefit, advantage, or equivalent to the public, regardless of whether it is or is not recited in the claims.
It will be understood that the terms and expressions used herein have the ordinary meaning as is accorded to such terms and expressions with respect to their corresponding respective areas of inquiry and study except where specific meanings have otherwise been set forth herein. Relational terms such as first and second and the like may be used solely to distinguish one entity or action from another without necessarily requiring or implying any actual such relationship or order between such entities or actions. The terms “comprises,” “comprising,” or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by “a” or “an” does not, without further constraints, preclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.
The Abstract of the Disclosure is provided to allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, it can be seen that various features are grouped together in various embodiments for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separately claimed subject matter.
This application claims priority to and benefit of U.S. Provisional Patent Application Ser. No. 61/403,262 filed Sep. 13, 2010, Attorney Docket No. 028080-0604, and entitled “Efficient Mapping of Tissue Properties From Unregistered Data With Low Signal-to-Noise Ratio,” the entire content of which is incorporated herein by reference.
Number | Date | Country | |
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61403262 | Sep 2010 | US |