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GB2621332B - A method and an artificial intelligence system for assessing an MRI image - Google Patents

A method and an artificial intelligence system for assessing an MRI image Download PDF

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Publication number
GB2621332B
GB2621332B GB2211511.7A GB202211511A GB2621332B GB 2621332 B GB2621332 B GB 2621332B GB 202211511 A GB202211511 A GB 202211511A GB 2621332 B GB2621332 B GB 2621332B
Authority
GB
United Kingdom
Prior art keywords
assessing
artificial intelligence
mri image
intelligence system
mri
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
GB2211511.7A
Other versions
GB2621332A (en
GB202211511D0 (en
Inventor
Hassn Alenaini Wareed
McInally Jamie
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Twinn Health Ltd
Original Assignee
Twinn Health Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Twinn Health Ltd filed Critical Twinn Health Ltd
Priority to GB2211511.7A priority Critical patent/GB2621332B/en
Publication of GB202211511D0 publication Critical patent/GB202211511D0/en
Priority to PCT/IB2023/057971 priority patent/WO2024033789A1/en
Publication of GB2621332A publication Critical patent/GB2621332A/en
Application granted granted Critical
Publication of GB2621332B publication Critical patent/GB2621332B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G06T2207/10088—Magnetic resonance imaging [MRI]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20081—Training; Learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20084—Artificial neural networks [ANN]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Radiology & Medical Imaging (AREA)
  • Quality & Reliability (AREA)
  • Magnetic Resonance Imaging Apparatus (AREA)
GB2211511.7A 2022-08-08 2022-08-08 A method and an artificial intelligence system for assessing an MRI image Active GB2621332B (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
GB2211511.7A GB2621332B (en) 2022-08-08 2022-08-08 A method and an artificial intelligence system for assessing an MRI image
PCT/IB2023/057971 WO2024033789A1 (en) 2022-08-08 2023-08-07 A method and an artificial intelligence system for assessing adiposity using abdomen mri image

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
GB2211511.7A GB2621332B (en) 2022-08-08 2022-08-08 A method and an artificial intelligence system for assessing an MRI image

Publications (3)

Publication Number Publication Date
GB202211511D0 GB202211511D0 (en) 2022-09-21
GB2621332A GB2621332A (en) 2024-02-14
GB2621332B true GB2621332B (en) 2024-09-11

Family

ID=84546258

Family Applications (1)

Application Number Title Priority Date Filing Date
GB2211511.7A Active GB2621332B (en) 2022-08-08 2022-08-08 A method and an artificial intelligence system for assessing an MRI image

Country Status (2)

Country Link
GB (1) GB2621332B (en)
WO (1) WO2024033789A1 (en)

Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180165808A1 (en) * 2016-06-27 2018-06-14 University Of Central Florida Research Foundation, Inc. System and method for image-based quantification of white and brown adipose tissue at the whole-body, organ and body-region levels
WO2019182520A1 (en) * 2018-03-22 2019-09-26 Agency For Science, Technology And Research Method and system of segmenting image of abdomen of human into image segments corresponding to fat compartments
CN110517241A (en) * 2019-08-23 2019-11-29 吉林大学第一医院 A method for automatic quantitative analysis of abdominal fat based on MRI IDEAL-IQ sequence
WO2020034469A1 (en) * 2018-08-13 2020-02-20 Beijing Ande Yizhi Technology Co., Ltd. Method and apparatus for classifying a brain anomaly based on a 3d mri image
US20200058126A1 (en) * 2018-08-17 2020-02-20 12 Sigma Technologies Image segmentation and object detection using fully convolutional neural network
WO2020190821A1 (en) * 2019-03-15 2020-09-24 Genentech, Inc. Deep convolutional neural networks for tumor segmentation with positron emission tomography
CN111709952A (en) * 2020-05-21 2020-09-25 无锡太湖学院 A dual-stream decoding convolutional neural network based on edge feature optimization for automatic segmentation of MRI brain tumors
CN111862087A (en) * 2020-08-03 2020-10-30 张政 Liver and pancreas steatosis distinguishing method based on deep learning
CN113205566A (en) * 2021-04-23 2021-08-03 复旦大学 Abdomen three-dimensional medical image conversion generation method based on deep learning
US20210383537A1 (en) * 2020-06-09 2021-12-09 Siemens Healthcare Gmbh Synthesis of contrast enhanced medical images
WO2022051290A1 (en) * 2020-09-02 2022-03-10 Genentech, Inc. Connected machine-learning models with joint training for lesion detection
CN114202545A (en) * 2020-08-27 2022-03-18 东北大学秦皇岛分校 UNet + + based low-grade glioma image segmentation method
CN114549417A (en) * 2022-01-20 2022-05-27 高欣 Abdominal fat quantification method based on deep learning and nuclear magnetic resonance Dixon

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2018222755A1 (en) * 2017-05-30 2018-12-06 Arterys Inc. Automated lesion detection, segmentation, and longitudinal identification
US11263749B1 (en) 2021-06-04 2022-03-01 In-Med Prognostics Inc. Predictive prognosis based on multimodal analysis

Patent Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180165808A1 (en) * 2016-06-27 2018-06-14 University Of Central Florida Research Foundation, Inc. System and method for image-based quantification of white and brown adipose tissue at the whole-body, organ and body-region levels
WO2019182520A1 (en) * 2018-03-22 2019-09-26 Agency For Science, Technology And Research Method and system of segmenting image of abdomen of human into image segments corresponding to fat compartments
WO2020034469A1 (en) * 2018-08-13 2020-02-20 Beijing Ande Yizhi Technology Co., Ltd. Method and apparatus for classifying a brain anomaly based on a 3d mri image
US20200058126A1 (en) * 2018-08-17 2020-02-20 12 Sigma Technologies Image segmentation and object detection using fully convolutional neural network
WO2020190821A1 (en) * 2019-03-15 2020-09-24 Genentech, Inc. Deep convolutional neural networks for tumor segmentation with positron emission tomography
CN110517241A (en) * 2019-08-23 2019-11-29 吉林大学第一医院 A method for automatic quantitative analysis of abdominal fat based on MRI IDEAL-IQ sequence
CN111709952A (en) * 2020-05-21 2020-09-25 无锡太湖学院 A dual-stream decoding convolutional neural network based on edge feature optimization for automatic segmentation of MRI brain tumors
US20210383537A1 (en) * 2020-06-09 2021-12-09 Siemens Healthcare Gmbh Synthesis of contrast enhanced medical images
CN111862087A (en) * 2020-08-03 2020-10-30 张政 Liver and pancreas steatosis distinguishing method based on deep learning
CN114202545A (en) * 2020-08-27 2022-03-18 东北大学秦皇岛分校 UNet + + based low-grade glioma image segmentation method
WO2022051290A1 (en) * 2020-09-02 2022-03-10 Genentech, Inc. Connected machine-learning models with joint training for lesion detection
CN113205566A (en) * 2021-04-23 2021-08-03 复旦大学 Abdomen three-dimensional medical image conversion generation method based on deep learning
CN114549417A (en) * 2022-01-20 2022-05-27 高欣 Abdominal fat quantification method based on deep learning and nuclear magnetic resonance Dixon

Also Published As

Publication number Publication date
GB2621332A (en) 2024-02-14
WO2024033789A1 (en) 2024-02-15
GB202211511D0 (en) 2022-09-21

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