# US 10,769,823 B2 · Image processing apparatus, magnetic resonance imaging apparatus, and storage medium > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,769,823 B2 - Document ID: US10769823B2 - Status: Granted - Kind: B2 - Application number: 15/996,556 - Filed: 2018-06-04 - Published: 2018-12-27 - Granted: 2020-09-08 - Earliest claimed: 2017-06-22 - Assignees: Canon Medical Systems Corporation - Applicants: Canon Medical Systems Corporation - Inventors: Takuma Igarashi; Ryo Shiroishi - Web page: https://patentgrep.com/patent/US10769823B2 ## CPC - G06T 12/30: Image post-processing, e.g. metal artefact correction - A61B 5/0042: {for the brain} - A61B 5/055: involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging - G01R 33/5602: {by filtering or weighting based on different relaxation times within the sample, e.g. T1 weighting using an inversion pulse} - G01R 33/5608: {Data processing and visualization specially adapted for MR, e.g. for feature analysis and pattern recognition on the basis of measured MR data, segmentation of measured MR data, edge contour detection on the basis of measured MR data, for enhancing measured MR data in terms of signal-to-noise ratio by means of noise filtering or apodization, for enhancing measured MR data in terms of resolution by means for deblurring, windowing, zero filling, or generation of gray-scaled images, colour-coded images or images displaying vectors instead of pixels (image data processing or generation, in general G06T)} - G06T 5/94: based on local image properties, e.g. for local contrast enhancement - A61B 5/4088: {Diagnosing of monitoring cognitive diseases, e.g. Alzheimer, prion diseases or dementia} - A61B 5/7267: {involving training the classification device} - G06T 2207/10088: Magnetic resonance imaging [MRI] - G06T 2207/20081: Training; Learning - G06T 2207/20084: Artificial neural networks [ANN] - G06T 2207/30016: Brain - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - 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) ## Abstract An image processing apparatus according to an embodiment includes a processing circuitry. The processing circuitry obtains an MR image acquired by a magnetic resonance imaging apparatus and related to a brain. The processing circuitry divides a region of the brain in the MR image, into plural regions. The processing circuitry sets a parameter value used in generation of a calculated image generated by synthetic MRI and related to the brain, such that a relation of contrast among regions included in the plural regions becomes a predetermined relation. The processing circuitry generates the calculated image by the synthetic MRI, by using the MR image and the parameter value. ## Claims ### Claim 1 An image processing apparatus, comprising: a processing circuitry configured to: obtain a magnetic resonance (MR) image acquired by a magnetic resonance imaging apparatus, the MR image being related to a brain of a subject; divide a region of the brain in the MR image, into plural regions; set a parameter value used to generate a calculated image related to the brain by synthetic MRI, such that a relation of contrast among regions included in the plural regions in the calculated image becomes a relation of contrast among the regions, the relation being predetermined for an image type of the calculated image or for a disease of the subject; and generate the calculated image by the synthetic MRI, by using a quantitative image derived from the MR image, and the set parameter value. ### Claim 2 (depends on 1) The image processing apparatus according to claim 1, wherein the processing circuitry sets the parameter value such that contrast among the regions satisfies a known contrast ratio corresponding to a specified image type. ### Claim 3 (depends on 2) The image processing apparatus according to claim 2, further comprising: a storage configured to store therein, for each image type, with respect to the contrast among the regions, information indicating the known contrast ratio corresponding to the image type, wherein the processing circuitry refers to the information stored in the storage, obtains the known contrast ratio corresponding the specified image type, and sets the parameter value such that the contrast among the regions satisfies the obtained contrast ratio. ### Claim 4 (depends on 2) The image processing apparatus according to claim 2, wherein the processing circuitry sets the parameter value by using a learnt model obtained by machine learning using, as a data set for learning, a quantitative image, an image type, and a correct answer value related to the parameter value used in the generation of the calculated image. ### Claim 5 (depends on 2) The image processing apparatus according to claim 2, wherein the processing circuitry receives, from an operator, an operation for specification of at least one region of the plural regions, and sets the parameter value such that contrast among remaining regions of the plural regions satisfies the known contrast ratio, the remaining regions excluding the at least one region. ### Claim 6 (depends on 1) The image processing apparatus according to claim 1, further comprising: a storage configured to store therein information indicating, for each disease, a region of the plural regions, the region being related to the disease, wherein the processing circuitry refers to the information stored in the storage, determines a region related to a specified disease, and sets the parameter value such that contrast between the determined region and another region is emphasized. ### Claim 7 (depends on 6) The image processing apparatus according to claim 6, wherein the storage stores therein, for each disease, information indicating a combination of at least two regions related to the disease, and the processing circuitry refers to the information stored in the storage, determines a combination of regions related to the specified disease, and sets the parameter value such that contrast among the regions included in the determined combination is emphasized. ### Claim 8 (depends on 6) The image processing apparatus according to claim 6, wherein the processing circuitry further updates the information indicating the region related to the disease, according to an operation from an operator. ### Claim 9 (depends on 6) The image processing apparatus according to claim 6, wherein the processing circuitry sets the parameter value such that contrast between the region related to the specified disease and a region peripheral to the region is emphasized. ### Claim 10 (depends on 6) The image processing apparatus according to claim 6, wherein the processing circuitry receives, from an operator, an operation for specification of an emphasis degree for contrast, and sets the parameter value, such that contrast between the determined region and the another region is emphasized at the specified emphasis degree. ### Claim 11 (depends on 1) The image processing apparatus according to claim 1, wherein the processing circuitry receives, from an operator, an operation for specification of a region of the plural regions, the region being related to a disease, and sets the parameter value, such that contrast between the region specified by the operator and another region is emphasized. ### Claim 12 (depends on 11) The image processing apparatus according to claim 11, wherein the processing circuitry sets the parameter value such that contrast between the region related to the specified disease and a region peripheral to the region is emphasized. ### Claim 13 (depends on 11) The image processing apparatus according to claim 11, wherein the processing circuitry receives, from an operator, an operation for specification of an emphasis degree for contrast, and sets the parameter value, such that contrast between the specified region and the another region is emphasized at the specified emphasis degree. ### Claim 14 (depends on 1) The image processing apparatus according to claim 1, wherein the processing circuitry: obtains a T1 weighted image acquired by the magnetic resonance imaging apparatus by use of a Magnetization Prepared 2 Rapid Gradient Echo (MP2RAGE) sequence, and a T1 map image derived from the T1 weighted image; divides the region of the brain into the plural regions by using the T1 weighted image; and generates the calculated image by using the T1 map image and the parameter value. ### Claim 15 An image processing apparatus, comprising: a processing circuitry configured to: obtain an input image related to a brain; divide a region of the brain in the input image, into plural regions; set a parameter value to generate a calculated image related to the brain, such that a relation of contrast among regions included in the plural regions in the calculated image becomes a relation of contrast among the regions, the relation being predetermined for an image type of the calculated image or for a disease of the subject; and generate the calculated image by using the input image and the set parameter value. ### Claim 16 A magnetic resonance imaging apparatus, comprising: a processing circuitry configured to: divide a region of a brain in a magnetic resonance (MR) image related to the brain, into plural regions; set a parameter value to generate a calculated image related to the brain by synthetic MRI, such that a relation of contrast among regions included in the plural regions in the calculated image becomes a relation of contrast among the regions, the relation being predetermined for an image type of the calculated image or for a disease of the subject; and generate the calculated image by the synthetic MRI, by using a quantitative image derived from the MR image, and the set parameter value. ### Claim 17 A non-transitory computer-readable storage medium having plural computer-executable commands recorded therein, the plural computer-executable commands causing the computer to execute: obtaining a magnetic resonance (MR) image acquired by a magnetic resonance imaging apparatus, the MR image being related to a brain; dividing a region of the brain in the MR image, into plural regions; setting a parameter value to generate a calculated image related to the brain by synthetic MM, such that a relation of contrast among regions included in the plural regions in the calculated image becomes a relation of contrast among the regions, the relation being predetermined for an image type of the calculated image or for a disease of the subject; and generating the calculated image by the synthetic MRI, by using a quantitative image derived from the MR image, and the set parameter value.