# US 10,373,351 B2 · Image reconstruction system and method in magnetic resonance imaging > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,373,351 B2 - Document ID: US10373351B2 - Status: Granted - Kind: B2 - Application number: 16/174,223 - Filed: 2018-10-29 - Published: 2019-03-07 - Granted: 2019-08-06 - Earliest claimed: 2016-11-07 - Assignees: Shanghai United Imaging Healthcare Co., Ltd. - Applicants: Shanghai United Imaging Healthcare Co., Ltd. - Inventors: Renjie He; Yu Ding; Qi Liu - Web page: https://patentgrep.com/patent/US10373351B2 ## CPC - A61B 5/055: involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging - A61B 5/7203: {for noise prevention, reduction or removal} - G01R 33/00: Arrangements or instruments for measuring magnetic variables - G01R 33/5611: {Parallel magnetic resonance imaging, e.g. sensitivity encoding [SENSE], simultaneous acquisition of spatial harmonics [SMASH], unaliasing by Fourier encoding of the overlaps using the temporal dimension [UNFOLD], k-t-broad-use linear acquisition speed-up technique [k-t-BLAST], k-t-SENSE (structural details of arrays of sub-coils G01R33/3415)} - G01R 33/5659: {caused by a distortion of the RF magnetic field, e.g. spatial inhomogeneities of the RF magnetic field (G01R33/56509, G01R33/56518, G01R33/56536 take precedence)} - G06T 5/70: Denoising; Smoothing - G06T 7/10: Segmentation; Edge detection (motion-based segmentation G06T7/215) - G06T 7/12: Edge-based segmentation - G06T 12/30: Image post-processing, e.g. metal artefact correction - A61B 2576/00: Medical imaging apparatus involving image processing or analysis (A61B1/00009, A61B6/52 and A61B8/52 take precedence) - G06T 2207/10088: Magnetic resonance imaging [MRI] - G06T 2207/20021: Dividing image into blocks, subimages or windows - G16H 30/40: for processing medical images, e.g. editing - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G01R: MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES (indicating correct tuning of resonant circuits H03J3/12) - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA ## Abstract A method and system for image reconstruction are provided. Multiple coil images may be obtained. A first reconstructed image based on the multiple coil images may be reconstructed based on a first reconstruction algorithm. A second reconstructed image based on the multiple coil images may be reconstructed based on a second reconstruction algorithm. Correction information about the first reconstructed image may be generated based on the first reconstructed image and the second reconstructed image. A third reconstructed image may be generated based on the first reconstructed image and the correction information about the first reconstructed image. ## Claims ### Claim 1 A method for reconstructing a corrected image implemented on a magnetic resonance imaging (MRI) system including an MRI device and a computing device, the MRI device including multiple radio frequency (RF) receiver coils, the computing device including a processor, the method comprising: receiving, by the multiple RF receiver coils, MR signals of an object; generating, by the processor, multiple coil images of the object based on the MR signals, the multiple coil images including a first set of coil images and a second set of coil images; reconstructing, by the processor, a first reconstructed image based on the first set of coil images according to a first reconstruction algorithm; reconstructing, by the processor, a second reconstructed image based on the second set of coil images according to a second reconstruction algorithm, the second reconstruction algorithm being different with the first reconstruction algorithm; generating, by the processor, correction information about the first reconstructed image by dividing the first reconstructed image by the second reconstructed image; and generating, by the processor, the corrected image with reduced inhomogeneity intensity based on the first reconstructed image and the correction information about the first reconstructed image. ### Claim 2 (depends on 1) The method of claim 1, the generating multiple coil images of the object based on the MR signals including: generating a coil image based on a first signal of the MR signals corresponding to a first RF receiver coil of the multiple RF receiver coils. ### Claim 3 (depends on 1) The method of claim 1, the first set of coil images being the same with the second set of coil images. ### Claim 4 (depends on 1) The method of claim 1, the first reconstruction algorithm or the second reconstruction algorithm including at least one of a sum of squares (SOS) algorithm, a geometric average (GA) algorithm, a sensitivity encoding (SENSE) algorithm, a parallel imaging with localized sensitivities (PILS) algorithm, a modified sensitivity encoding (MSENSE) algorithm, or a SPACE RIP algorithm. ### Claim 5 (depends on 1) The method of claim 1, wherein the reconstructing a first reconstructed image or the reconstructing a second reconstructed image further includes: for each point of a plurality of points in the imaged object determining pixel coordinates of corresponding pixels in the multiple coil images relating to the point of the imaged object; and obtaining pixel values of the corresponding pixels in the multiple coil images of the point; and reconstructing the first reconstructed image or the second reconstructed image based on the pixel coordinates and the pixel values of the corresponding pixels in the multiple coil images of the plurality of points in the imaged object. ### Claim 6 (depends on 1) The method of claim 1, wherein the correction information includes a divided image, and the generating the corrected image further includes: dividing the first reconstructed image by the divided image. ### Claim 7 (depends on 1) The method of claim 1, wherein the correction information includes a divided image, and the generating correction information further includes: smoothing the divided image to generate a smoothed divided image; and normalizing the smoothed divided image to generate a normalized image. ### Claim 8 (depends on 7) The method of claim 7, wherein the generating the corrected image further includes: dividing the first reconstructed image by the normalized image. ### Claim 9 A system comprising an MRI device and a computing device, the MRI device including multiple radio frequency (RF) receiver coils, the computing device including a processor, wherein during operation, the processor causes the system to: receive, by the multiple RF receiver coils, MR signals of an object; generate, by the processor, multiple coil images of the object based on the MR signals, the multiple coil images including a first set of coil images and a second set of coil images; generate, by the processor, a first reconstructed image based on the first set of coil images according to a first reconstruction algorithm and generate a second reconstructed image based on the second set of coil images according to a second reconstruction algorithm, the second reconstruction algorithm being different with the first reconstruction algorithm; generate, by the processor, correction information about the first reconstructed image by dividing the first reconstructed image by the second reconstructed image; and generate, by the processor, a corrected image with reduced inhomogeneity intensity based on the first reconstructed image and the correction information about the first reconstructed image. ### Claim 10 (depends on 9) The system of claim 9, the generate multiple coil images of the object based on the MR signals including: generating a coil image based on a first signal of the MR signals corresponding to a first RF receiver coil of the multiple RF receiver coils. ### Claim 11 (depends on 9) The system of claim 9, the first set of coil images being the same with the second set of coil images. ### Claim 12 (depends on 9) The system of claim 9, the first reconstruction algorithm or the second reconstruction algorithm including at least one of a sum of squares (SOS) algorithm, a geometric average (GA) algorithm, a sensitivity encoding (SENSE) algorithm, a parallel imaging with localized sensitivities (PILS) algorithm, a modified sensitivity encoding (MSENSE) algorithm, or a SPACE RIP algorithm. ### Claim 13 (depends on 9) The system of claim 9, wherein to generate the first reconstructed image or to generate the second reconstructed image, the processor further causes the system to: for each point of a plurality of points in the imaged object determine pixel coordinates of corresponding pixels in the multiple coil images relating to the point of the imaged object; obtain pixel values of the corresponding pixels in the multiple coil images of the point; and generate the first reconstructed image or the second reconstructed image based on the pixel coordinates and the pixel values of the corresponding pixels in the multiple coil images of the plurality of points in the imaged object. ### Claim 14 (depends on 9) The system of claim 9, wherein the correction information includes a divided image, and to generate the corrected image, the processor further causes the system to: divide the first reconstructed image by the divided image. ### Claim 15 (depends on 9) The system of claim 9, wherein the correction information includes a divided image, and to generate the correction information, the processor further causes the system to: smooth the divided image to generate a smoothed divided image; and normalize the smoothed divided image to generate a normalized image. ### Claim 16 (depends on 15) The system of claim 15, wherein to generate the corrected image, the processor further causes the system to: divide the first reconstructed image by the normalized image. ### Claim 17 A non-transitory computer readable medium comprising executable instructions that, when executed by at least one processor, cause the at least one processor to effectuate a method comprising: receiving MR signals of an object, the MR signals being acquired by multiple RF receiver coils of an MR device; generating, by the at least one processor, multiple coil images of the object based on the MR signals, the multiple coil images including a first set of coil images and a second set of coil images; reconstructing, by the at least one processor, a first reconstructed image based on the first set of coil images based on a first reconstruction algorithm; reconstructing, by the at least one processor, a second reconstructed image based on the second set of coil images based on a second reconstruction algorithm, the second reconstruction algorithm being different with the first reconstruction algorithm; generating, by the at least one processor, correction information about the first reconstructed image by dividing the first reconstructed image by the second reconstructed image; and generating, by the at least one processor, a corrected image with reduced inhomogeneity intensity based on the first reconstructed image and the correction information about the first reconstructed image. ### Claim 18 (depends on 17) The non-transitory computer readable medium of claim 17, the generating multiple coil images of the object based on the MR signals including: generating a coil image based on a first signal of the MR signals corresponding to a first RF receiver coil of the multiple RF receiver coils. ### Claim 19 (depends on 17) The non-transitory computer readable medium of claim 17, the first set of coil images being the same with the second set of coil images. ### Claim 20 (depends on 17) The non-transitory computer readable medium of claim 17, the first reconstruction algorithm or the second reconstruction algorithm including at least one of a sum of squares (SOS) algorithm, a geometric average (GA) algorithm, a sensitivity encoding (SENSE) algorithm, a parallel imaging with localized sensitivities (PILS) algorithm, a modified sensitivity encoding (MSENSE) algorithm, or a SPACE RIP algorithm.