Abstract:
A system and corresponding method for multicoil image analysis are provided, the system including a processor, an imaging adapter in signal communication with the processor for receiving image data from each of a plurality of individual coils, an analysis unit in signal communication with the processor for analyzing the individual coil image data, and a reconstruction unit in signal communication with the processor for reconstructing a composite image or coil images from the individual coil image data; and the method including receiving image data from each of a plurality of individual coils, analyzing the individual coil image data, and reconstructing a composite image or coil images from the individual coil image data.

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application claims the benefit of U.S. Provisional Application Ser. No. 60/538,042, filed Jan. 20, 2004 and entitled “Multicoil Image Analysis for Magnetic Resonance Image Segmentation, Registration, and Reconstruction”, which is incorporated herein by reference in its entirety. 
    
    
     BACKGROUND 
     Medical image scanning data, for example, is typically obtained in the form of slices in various types of imaging modalities. These slices are then stacked to form a three-dimensional (3D) volume. 
     In the case of cardiovascular applications, for example, image registration and segmentation is often difficult in magnetic resonance (MR) imaging due to a lack of contrast between features, and/or due to artifacts in the images. This problem is compounded when fast imaging methods are used at the price of the signal-to-noise ratio (SNR). 
     Existing approaches to image registration and segmentation work with varying degrees of success, and some are dependent on a priori knowledge of the structure under investigation. Accordingly, it is desirable in many cardiovascular applications to have an automatic, accurate and robust technique for image registration and segmentation, particularly where an organ is in motion. 
     SUMMARY 
     These and other drawbacks and disadvantages of the prior art are addressed by a system and method of multicoil image analysis for magnetic resonance image segmentation, registration, and reconstruction. 
     A system for multicoil image analysis includes a processor, an imaging adapter in signal communication with the processor for receiving image data from each of a plurality of individual coils, an analysis unit in signal communication with the processor for analyzing the individual coil image data, and a reconstruction unit in signal communication with the processor for reconstructing a composite image or individual coil images from the individual coil image data. 
     A corresponding method for multicoil image analysis includes receiving image data from each of a plurality of individual coils, analyzing the individual coil image data, and reconstructing a composite image or individual coil images from the individual coil image data. 
     These and other aspects, features and advantages of the present disclosure will become apparent from the following description of exemplary embodiments, which is to be read in connection with the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The present disclosure teaches a system and method of multicoil image analysis for magnetic resonance image segmentation, registration, and reconstruction, in accordance with the following exemplary figures, in which: 
         FIG. 1  shows a schematic diagram of a system for multicoil image analysis in accordance with an illustrative embodiment of the present disclosure; 
         FIG. 2  shows a flow diagram of a method for multicoil image analysis in accordance with an illustrative embodiment of the present disclosure; 
         FIG. 3  shows a graphical diagram of an individual surface coil image of relatively high contrast in accordance with an illustrative embodiment of the present disclosure; 
         FIG. 4  shows a graphical diagram of an individual surface coil image in accordance with an illustrative embodiment of the present disclosure; 
         FIG. 5  shows a graphical diagram of an individual surface coil image in accordance with an illustrative embodiment of the present disclosure; 
         FIG. 6  shows a graphical diagram of an individual surface coil image of relatively low contrast in accordance with an illustrative embodiment of the present disclosure; 
         FIG. 7  shows a graphical diagram of an individual surface coil image in accordance with an illustrative embodiment of the present disclosure; 
         FIG. 8  shows a graphical diagram of an individual surface coil image in accordance with an illustrative embodiment of the present disclosure; 
         FIG. 9  shows a graphical diagram of an individual surface coil image of relatively high contrast in accordance with an illustrative embodiment of the present disclosure; and 
         FIG. 10  shows a graphical diagram of an individual surface coil image in accordance with an illustrative embodiment of the present disclosure. 
     
    
    
     DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS 
     Image registration and segmentation is often difficult in magnetic resonance (MR) imaging, for example, due to at least a lack of contrast between features and/or artifacts in the images. This problem may be compounded when fast imaging methods are used to the detriment of the signal-to-noise ratio (SNR). An exemplary embodiment of the present disclosure adds information for segmentation by acquiring images with slightly different contrasts and combining the image information to identify tissues. The embodiment uses individual images from local radio frequency (RF) coils to glean differences in contrast for the purposes of segmentation, registration, coil selection, and/or reconstruction. A composite image reconstructed from the individual RF coils may also be used for further refinement of segmentation or registration, and is amenable to inline processing. 
     As shown in  FIG. 1 , a system for multicoil image analysis for magnetic resonance image segmentation, registration, and reconstruction, according to an illustrative embodiment of the present disclosure, is indicated generally by the reference numeral  100 . The system  100  includes at least one processor or central processing unit (CPU)  102  in signal communication with a system bus  104 . A read only memory (ROM)  106 , a random access memory (RAM)  108 , a display adapter  110 , an I/O adapter  112 , a user interface adapter  114 , a communications adapter  128 , and an imaging adapter  130  are also in signal communication with the system bus  104 . A display unit  116  is in signal communication with the system bus  104  via the display adapter  110 . A disk storage unit  118 , such as, for example, a magnetic or optical disk storage unit is in signal communication with the system bus  104  via the I/O adapter  112 . A mouse  120 , a keyboard  122 , and an eye tracking device  124  are in signal communication with the system bus  104  via the user interface adapter  114 . A magnetic resonance imaging device  132  is in signal communication with the system bus  104  via the imaging adapter  130 . 
     An image analysis unit  172  and an image reconstruction unit  180  are also included in the system  100  and in signal communication with the CPU  102  and the system bus  104 . While the image analysis unit  172  and the image reconstruction unit  180  are illustrated as coupled to the at least one processor or CPU  102 , these components are preferably embodied in computer program code stored in at least one of the memories  106 ,  108  and  118 , wherein the computer program code is executed by the CPU  102 . As will be recognized by those of ordinary skill in the pertinent art based on the teachings herein, alternate embodiments are possible, such as, for example, embodying some or all of the computer program code in registers located on the processor chip  102 . Given the teachings of the disclosure provided herein, those of ordinary skill in the pertinent art will contemplate various alternate configurations and implementations of the image analysis unit  172  and the image reconstruction unit  180 , as well as the other elements of the system  100 , while practicing within the scope and spirit of the present disclosure. 
     Turning to  FIG. 2 , a flowchart for multicoil image analysis for magnetic resonance image segmentation, registration, and reconstruction, according to an illustrative embodiment of the present disclosure, is indicated generally by the reference numeral  200 . The flowchart  200  includes a start block  210  that passes control to a function block  212 . The function block  212  initiates individual coils for scanning and passes control to an input block  214 . The input block  214  receives individual coil scan data and passes control to a decision block  216 . 
     The decision block  216  checks whether to analyze the raw coil data, and if so, passes control to a function block  218 . The function block  218  analyzes the individual coil image data, such as by profiling intensities, for example, and performs registration and/or segmentation in the raw data space. The block  218  passes control to a decision block  220 . The decision block  220  checks whether to reconstruct individual coil images, and if so, passes control to a function block  222 . If not, the block  220  passes control to a block  224 . The function block  222  performs reconstruction of individual coil images from the coil data, and passes control to the decision block  224 . The decision block  224  checks whether to reconstruct a combined composite image, and if so, passes control to a function block  226 . If not, the block  224  passes control to a block  228 . The function block  226  performs reconstruction of a composite image from the individual coil image data, and passes control to the function block  228 . The function block  228  analyzes the image data and performs registration and/or segmentation responsive to the analysis, and passes control to an output block  240 . 
     If, on the other hand, the decision block  216  determines not to analyze the raw coil data, it passes control to a decision block  230  to check whether to reconstruct individual coil images. If not, the block  230  passes control to a block  234 , and if so, the block  230  passes control to a function block  232  to reconstruct individual images from the coil data. The block  232  passes control to the decision block  234  to check whether to reconstruct a combined image, and if so, passes control to a function block  236  to reconstruct the combined image from the coil data. If not, the block  234  passes control to a block  238 . The block  236  passes control to the function block  238 . The block  238  performs registration and/or segmentation in the image data space, and passes control to the output block  240 . 
     The output block  240 , in turn, presents the final image, and passes control to an end block  242 . One or more of the function blocks  218 ,  228  and  238  may use the analyzed coil image data and/or profiled coil image intensities to supplement the information contained in the composite image. 
     Turning now to  FIG. 3 , an individual image of high contrast constructed from a small surface coil is indicated generally by the reference numeral  300 . The image  300  includes an intensity path  310 , here having a length of about 7.48 centimeters, which has an intensity profile  312  that is displayed here over the image merely for descriptive purposes. The instant intensity profile  312  has a range of about 79 to about 578. 
     As shown in  FIG. 4 , an individual image constructed from a small surface coil is indicated generally by the reference numeral  400 . The image  400  includes an intensity path  410 , here having a length of about 7.49 centimeters, which has an intensity profile  412  that is displayed here over the image merely for descriptive purposes. The instant intensity profile  412  has a range of about 11 to about 168. 
     Turning to  FIG. 5 , an individual image constructed from a small surface coil is indicated generally by the reference numeral  500 . The image  500  includes an intensity path  510 , here having a length of about 7.48 centimeters, which has an intensity profile  512  that is displayed here over the image merely for descriptive purposes. The instant intensity profile  512  has a range of about 15 to about 160. 
     Turning now to  FIG. 6 , an individual image of rather low contrast constructed from a small surface coil is indicated generally by the reference numeral  600 . The image  600  includes an intensity path  610 , here having a length of about 7.37 centimeters, which has an intensity profile  612  that is displayed here over the image merely for descriptive purposes. The instant intensity profile  612  has a range of about 4 to about 70. 
     As shown in  FIG. 7 , an individual image constructed from a small surface coil is indicated generally by the reference numeral  700 . The image  700  includes an intensity path  710 , here having a length of about 7.40 centimeters, which has an intensity profile  712  that is displayed here over the image merely for descriptive purposes. The instant intensity profile  712  has a range of about 4 to about 128. 
     Turning to  FIG. 8 , an individual image constructed from a small surface coil is indicated generally by the reference numeral  800 . The image  800  includes an intensity path  810 , here having a length of about 7.49 centimeters, which has an intensity profile  812  that is displayed here over the image merely for descriptive purposes. The instant intensity profile  812  has a range of about 11 to about 221. 
     Turning now to  FIG. 9 , an individual image of relatively high contrast constructed from a small surface coil is indicated generally by the reference numeral  900 . The image  900  includes an intensity path  910 , here having a length of about 7.64 centimeters, which has an intensity profile  912  that is displayed here over the image merely for descriptive purposes. The instant intensity profile  912  has a range of about 42 to about 418. 
     As shown in  FIG. 10 , an individual image constructed from a small surface coil is indicated generally by the reference numeral  1000 . The image  1000  includes an intensity path  1010 , here having a length of about 7.48 centimeters, which has an intensity profile  1012  that is displayed here over the image merely for descriptive purposes. The instant intensity profile  1012  has a range of about 16 to about 285. 
     In the images  300  through  1000  of  FIGS. 3 through 10 , respectively, the individual images reconstructed from small surface coils are shown, which may be used for partial parallel imaging, as well as the image intensity profiles across each image. The profile across the heart for each case is different in each image. However, some features of the profile of the heart region are consistent, and these consistencies can be used to define tissue borders, for example. Even the individual images of relatively lower contrast contribute useful information. 
     The spatial variations may be used as profiles or two-dimensional (2D) maps of signal intensity, and input to a segmentation or registration process to give additional information not present in a single image. Since the locations of the coils are known with respect to the underlying anatomy, the coil position and lack or presence of a signal variation also provides useful information. Registration of time series of images or different sub-modalities of MR images may also be attained using the additional information. Alternate applications include automatic coil selection based on analysis of noise and signal profile contents of each image, and providing input to reconstruction methods for partial parallel imaging. 
     In operation, images formed from various coil elements are spatially registered, and these inherently provide varied contrast to serve as input for a segmentation and/or registration step. The preprocessing of the data from individual coil elements may be done as part of the image reconstruction, thus making it rapid and efficient. Analysis of time-series of data from the individual coil elements may be used as input for registration and/or segmentation processing. Image data may be used to enhance the reconstruction of data. Alternate embodiments may include varying contrast in the set of individual coil images for additional input information. 
     Thus, preferred embodiments use data in a pre-final-image reconstruction mode, in accordance with coil-dependent varying signals, as a basis for segmentation, registration, coil selection and/or image reconstruction. In addition, raw data of the individual coil images is used as a basis for segmentation and/or registration. 
     These and other features and advantages of the present disclosure may be readily ascertained by one of ordinary skill in the pertinent art based on the teachings herein. It is to be understood that the teachings of the present disclosure may be implemented in various forms of hardware, software, firmware, special purpose processors, or combinations thereof. 
     Most preferably, the teachings of the present disclosure are implemented as a combination of hardware and software. Moreover, the software is preferably implemented as an application program tangibly embodied on a program storage unit. The application program may be uploaded to, and executed by, a machine comprising any suitable architecture. Preferably, the machine is implemented on a computer platform having hardware such as one or more central processing units (CPU), a random access memory (RAM), and input/output (I/O) interfaces. 
     The computer platform may also include an operating system and microinstruction code. The various processes and functions described herein may be either part of the microinstruction code or part of the application program, or any combination thereof, which may be executed by a CPU. In addition, various other peripheral units may be connected to the computer platform such as an additional data storage unit and a printing unit. 
     It is to be further understood that, because some of the constituent system components and methods depicted in the accompanying drawings are preferably implemented in software, the actual connections between the system components or the process function blocks may differ depending upon the manner in which the present disclosure is programmed. Given the teachings herein, one of ordinary skill in the pertinent art will be able to contemplate these and similar implementations or configurations of the present disclosure. 
     Although the illustrative embodiments have been described herein with reference to the accompanying drawings, it is to be understood that the present disclosure is not limited to those precise embodiments, and that various changes and modifications may be effected therein by one of ordinary skill in the pertinent art without departing from the scope or spirit of the present disclosure. All such changes and modifications are intended to be included within the scope of the present disclosure as set forth in the appended claims.