CA3201789A1 - System and method for domain generalization across variations in medical images - Google Patents

System and method for domain generalization across variations in medical images

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Publication number
CA3201789A1
CA3201789A1 CA3201789A CA3201789A CA3201789A1 CA 3201789 A1 CA3201789 A1 CA 3201789A1 CA 3201789 A CA3201789 A CA 3201789A CA 3201789 A CA3201789 A CA 3201789A CA 3201789 A1 CA3201789 A1 CA 3201789A1
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CA
Canada
Prior art keywords
images
image data
training
frames
captured image
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.)
Pending
Application number
CA3201789A
Other languages
English (en)
French (fr)
Inventor
Edward Chen
John GALEOTTI
Howie Choset
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.)
Carnegie Mellon University
Original Assignee
Carnegie Mellon University
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 Carnegie Mellon University filed Critical Carnegie Mellon University
Publication of CA3201789A1 publication Critical patent/CA3201789A1/en
Pending legal-status Critical Current

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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/082—Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/044—Recurrent networks, e.g. Hopfield networks
    • G06N3/0442—Recurrent networks, e.g. Hopfield networks characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G06N3/0455—Auto-encoder networks; Encoder-decoder networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/0464—Convolutional networks [CNN, ConvNet]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/047—Probabilistic or stochastic networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/0475—Generative networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/09—Supervised learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/091—Active learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/094—Adversarial learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computing arrangements based on specific mathematical models
    • G06N7/01—Probabilistic graphical models, e.g. probabilistic networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/774—Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00—Indexing scheme relating to image or video recognition or understanding
    • G06V2201/03—Recognition of patterns in medical or anatomical images

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Evolutionary Computation (AREA)
  • Software Systems (AREA)
  • General Physics & Mathematics (AREA)
  • Computing Systems (AREA)
  • Artificial Intelligence (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Data Mining & Analysis (AREA)
  • General Engineering & Computer Science (AREA)
  • Mathematical Physics (AREA)
  • Computational Linguistics (AREA)
  • Biophysics (AREA)
  • Molecular Biology (AREA)
  • Biomedical Technology (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Medical Informatics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Databases & Information Systems (AREA)
  • Multimedia (AREA)
  • Probability & Statistics with Applications (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Radiology & Medical Imaging (AREA)
  • Epidemiology (AREA)
  • Primary Health Care (AREA)
  • Public Health (AREA)
  • Algebra (AREA)
  • Computational Mathematics (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Pure & Applied Mathematics (AREA)
  • Image Analysis (AREA)
  • Image Processing (AREA)
  • Magnetic Resonance Imaging Apparatus (AREA)
CA3201789A 2020-11-13 2021-11-15 System and method for domain generalization across variations in medical images Pending CA3201789A1 (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US202063113397P 2020-11-13 2020-11-13
US63/113,397 2020-11-13
PCT/US2021/059356 WO2022104194A1 (en) 2020-11-13 2021-11-15 System and method for domain generalization across variations in medical images

Publications (1)

Publication Number Publication Date
CA3201789A1 true CA3201789A1 (en) 2022-05-19

Family

ID=81602649

Family Applications (1)

Application Number Title Priority Date Filing Date
CA3201789A Pending CA3201789A1 (en) 2020-11-13 2021-11-15 System and method for domain generalization across variations in medical images

Country Status (7)

Country Link
US (1) US12154319B2 (https=)
JP (1) JP2023552284A (https=)
KR (1) KR20230107320A (https=)
CN (1) CN116601670A (https=)
CA (1) CA3201789A1 (https=)
IL (1) IL302903A (https=)
WO (1) WO2022104194A1 (https=)

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KR20230084967A (ko) * 2021-12-06 2023-06-13 삼성전자주식회사 반도체 공정 이미지 생성기를 훈련시키는 방법
KR102831324B1 (ko) * 2022-12-16 2025-07-07 아주대학교산학협력단 대표 패턴 기반 의료 영상의 투과 상태 품질을 평가하는 방법 및 장치
KR20250059151A (ko) 2023-10-24 2025-05-02 연세대학교 산학협력단 도메인 일반화된 분할 모델 학습 방법
US20250227198A1 (en) * 2024-01-10 2025-07-10 Beth Israel Deaconess Medical Center, Inc. System and method for image temporal interpolation for dynamic imaging
WO2025150976A1 (ko) * 2024-01-12 2025-07-17 주식회사 필드큐어 의료영상을 이용한 조직 분할 방법
CN118096567B (zh) * 2024-02-27 2024-10-25 湖北经济学院 基于贝叶斯方法的dbn模型自适应图像去噪方法和系统
CN119477845B (zh) * 2024-11-04 2025-06-13 中国人民解放军南部战区总医院 一种基于跨模态知识融合的心肌梗死定位方法
CN120125827B (zh) * 2025-05-12 2025-07-29 复影(上海)医疗科技有限公司 基于多模态mri的脑肿瘤分割方法及系统

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US7418128B2 (en) 2003-07-31 2008-08-26 Microsoft Corporation Elastic distortions for automatic generation of labeled data
US20100165087A1 (en) * 2008-12-31 2010-07-01 Corso Jason J System and method for mosaicing endoscope images captured from within a cavity
GB201603645D0 (en) * 2016-03-02 2016-04-13 Univ Edinburgh Frame selection in medical image data
US10667776B2 (en) 2016-08-11 2020-06-02 Siemens Healthcare Gmbh Classifying views of an angiographic medical imaging system
US10878529B2 (en) * 2017-12-22 2020-12-29 Canon Medical Systems Corporation Registration method and apparatus
JP7062960B2 (ja) * 2018-01-12 2022-05-09 株式会社リコー 情報処理システム、プログラム、情報処理装置及び情報出力方法
US11580381B2 (en) * 2018-08-01 2023-02-14 Siemens Healthcare Gmbh Complex-valued neural network with learnable non-linearities in medical imaging
US10771698B2 (en) * 2018-08-31 2020-09-08 Qualcomm Incorporated Image stabilization using machine learning
KR102015939B1 (ko) * 2018-09-27 2019-08-28 주식회사 크라우드웍스 인공지능 영상 학습을 위한 동영상의 학습 대상 프레임 이미지 샘플링 방법, 장치, 프로그램 및 그 영상 학습 방법
TWI728369B (zh) * 2019-05-24 2021-05-21 臺北醫學大學 人工智慧雲端膚質與皮膚病灶辨識方法及其系統
JP7451443B2 (ja) * 2021-02-09 2024-03-18 キヤノン株式会社 画像処理方法および装置、機械学習モデルの訓練方法および装置、並びにプログラム
DE102021202813A1 (de) * 2021-03-23 2022-09-29 Robert Bosch Gesellschaft mit beschränkter Haftung Verfahren, Vorrichtung und Computerprogramm für eine Unsicherheitsbewertung einer Bildklassifikation
US12266157B2 (en) * 2021-04-06 2025-04-01 Nec Corporation Temporal augmentation for training video reasoning system

Also Published As

Publication number Publication date
KR20230107320A (ko) 2023-07-14
JP2023552284A (ja) 2023-12-15
IL302903A (en) 2023-07-01
CN116601670A (zh) 2023-08-15
US12154319B2 (en) 2024-11-26
WO2022104194A1 (en) 2022-05-19
US20240029410A1 (en) 2024-01-25

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