# US 11,112,477 B2 · Magnetic resonance imaging apparatus and image processing apparatus

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- Number: US 11,112,477 B2
- Document ID: US11112477B2
- Status: Granted
- Kind: B2
- Application number: 16/209,531
- Filed: 2018-12-04
- Published: 2019-04-11
- Granted: 2021-09-07
- Earliest claimed: 2013-08-20
- Assignees: Canon Medical Systems Corporation
- Applicants: Kyoto University; Canon Medical Systems Corporation
- Inventors: Yasutaka Fushimi; Naotaka Sakashita
- Web page: https://patentgrep.com/patent/US11112477B2

## CPC

- 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)}
- A61B 5/055: involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
- A61B 5/4064: {Evaluating the brain (for intracranial pressure A61B5/031; for cerebral blood gases A61B5/14553; using EEG A61B5/369)}
- A61B 5/4566: {Evaluating the spine (A61B5/4561 takes precedence)}
- A61B 5/704: {Tables}
- A61B 5/7289: {Retrospective gating, i.e. associating measured signals or images with a physiological event after the actual measurement or image acquisition, e.g. by simultaneously recording an additional physiological signal during the measurement or image acquisition}
- G06T 7/0012: {Biomedical image inspection}
- G06T 7/11: Region-based segmentation
- G06T 7/143: involving probabilistic approaches, e.g. Markov random field [MRF] modelling
- A61B 5/14507: {specially adapted for measuring characteristics of body fluids other than blood (devices for taking samples of body liquids A61B10/0045)}
- A61B 5/14542: {for measuring blood gases (A61B5/14551 takes precedence)}
- A61B 2576/026: for the brain
- G01R 33/5602: {by filtering or weighting based on different relaxation times within the sample, e.g. T1 weighting using an inversion pulse}
- G01R 33/5617: {using RF refocusing, e.g. RARE}
- G01R 33/5673: {Gating or triggering based on a physiological signal other than an MR signal, e.g. ECG gating or motion monitoring using optical systems for monitoring the motion of a fiducial marker}
- G06T 2207/10088: Magnetic resonance imaging [MRI]
- G06T 2207/30016: Brain
- G01R: MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES (indicating correct tuning of resonant circuits H03J3/12)
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL

## Abstract

A magnetic resonance imaging apparatus according to an embodiment includes a sequence controller and a storage unit. The sequence controller acquires magnetic resonance signals of a target imaging part including cerebrospinal fluid flowing therein of a subject in a condition where a supply of oxygen is receivable, at a plurality of time phases in an oxygen inhalation process of the subject. The storage unit stores therein the magnetic resonance signals acquired at the time phases.

## Claims

### Claim 1

An image processing apparatus comprising:
processing circuitry configured to:
extract a cerebrospinal fluid (CSF) region including a cerebral ventricle portion region and a cerebral sulcus portion region from a magnetic resonance (MR) image;
receive an input to specify the cerebral ventricle portion region on the MR image from which the CSF region is extracted; and
extract the cerebral sulcus portion region from the CSF region, based on the specified cerebral ventricle portion region.

### Claim 2 (depends on 1)

The image processing apparatus according to claim 1, wherein the processing circuitry is configured to receive an input to specify a region of interest (ROI) that encompasses the cerebral ventricle portion region.

### Claim 3 (depends on 1)

The image processing apparatus according to claim 1, wherein the processing circuitry is configured to generate a mask of the cerebral sulcus portion region by using the CSF region and the specified cerebral ventricle portion region.

### Claim 4 (depends on 3)

The image processing apparatus according to claim 3, wherein the processing circuitry is configured to generate the mask of the cerebral sulcus portion region by subtracting a mask of the cerebral ventricle portion region from the CSF region.

### Claim 5 (depends on 4)

The image processing apparatus according to claim 4, wherein the processing circuitry is configured to apply the mask of the cerebral sulcus portion region and the mask of the cerebral ventricle portion region to the MR image, and extracts signal values of the cerebral sulcus portion region and the cerebral ventricle portion region.

### Claim 6

An image processing apparatus comprising:
processing circuitry configured to:
extract a cerebrospinal fluid (CSF) region including a cerebral ventricle portion region and a cerebral sulcus portion region from a magnetic resonance (MR) image;
identify the cerebral ventricle portion region on the MR image from which the CSF region is extracted; and
extract the cerebral sulcus portion region from the CSF region, based on the identified cerebral ventricle portion region.

### Claim 7

An image processing method comprising:
extracting a cerebrospinal fluid (CSF) region including a cerebral ventricle portion region and a cerebral sulcus portion region from a magnetic resonance (MR) image;
receiving an input to specify the cerebral ventricle portion region on the MR image from which the CSF region is extracted; and
extracting the cerebral sulcus portion region from the CSF region, based on the specified cerebral ventricle portion region.

### Claim 8

An image processing method comprising:
extracting a cerebrospinal fluid (CSF) region including a cerebral ventricle portion region and a cerebral sulcus portion region from a magnetic resonance (MR) image;
identifying the cerebral ventricle portion region on the MR image from which the CSF region is extracted; and
extracting the cerebral sulcus portion region from the CSF region, based on the identified cerebral ventricle portion region.