IN2012DN02620A - - Google Patents

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Publication number
IN2012DN02620A
IN2012DN02620A IN2620DEN2012A IN2012DN02620A IN 2012DN02620 A IN2012DN02620 A IN 2012DN02620A IN 2620DEN2012 A IN2620DEN2012 A IN 2620DEN2012A IN 2012DN02620 A IN2012DN02620 A IN 2012DN02620A
Authority
IN
India
Prior art keywords
images
labelled
unlabelled
selected image
labelling
Prior art date
Application number
Inventor
Jan Paul Daniel Rueckert
Robin Wolz
Paul Aljabar
Original Assignee
Imp Innovations 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 Imp Innovations Ltd filed Critical Imp Innovations Ltd
Publication of IN2012DN02620A publication Critical patent/IN2012DN02620A/en

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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
    • G06F18/2137—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods based on criteria of topology preservation, e.g. multidimensional scaling or self-organising maps
    • G06F18/21375—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods based on criteria of topology preservation, e.g. multidimensional scaling or self-organising maps involving differential geometry, e.g. embedding of pattern manifold
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/149—Segmentation; Edge detection involving deformable models, e.g. active contour models
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/42—Global feature extraction by analysis of the whole pattern, e.g. using frequency domain transformations or autocorrelation
    • G06V10/422—Global feature extraction by analysis of the whole pattern, e.g. using frequency domain transformations or autocorrelation for representing the structure of the pattern or shape of an object therefor
    • 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
    • G06V10/7715—Feature extraction, e.g. by transforming the feature space, e.g. multi-dimensional scaling [MDS]; Mappings, e.g. subspace methods
    • 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
    • G06T2207/20112—Image segmentation details
    • G06T2207/20128—Atlas-based segmentation
    • 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
    • G06T2207/30016—Brain

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Software Systems (AREA)
  • Multimedia (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Databases & Information Systems (AREA)
  • Medical Informatics (AREA)
  • General Health & Medical Sciences (AREA)
  • Computing Systems (AREA)
  • Health & Medical Sciences (AREA)
  • Data Mining & Analysis (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • General Engineering & Computer Science (AREA)
  • Magnetic Resonance Imaging Apparatus (AREA)
  • Apparatus For Radiation Diagnosis (AREA)

Abstract

A method of processing medical images, performed by a computer processor and compulsing the steps of: (a) obtaining one or more atlases containing one or more images in which one or more anatomical features have been labelled with label data (b) obtaining a plurality of unlabelled images; (c) comparing the labelled and unlabelled images and selecting one or more unlabelled images that most closely resemble(s) one or more of the labelled images; (d) to each of those selected image(s), propagating label data from one or more of the closest of the labelled images, thereby labelling the corresponding anatomical feature(s) of each of the selected image(s) and causing the selected image(s) to become labelled image(s); and (e) iteratively repeating from step (c), thereby labelling others of the unlabelled images.
IN2620DEN2012 2009-09-30 2010-09-30 IN2012DN02620A (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
GBGB0917154.7A GB0917154D0 (en) 2009-09-30 2009-09-30 Method and apparatus for processing medical images
PCT/GB2010/001844 WO2011039515A1 (en) 2009-09-30 2010-09-30 Method and apparatus for processing medical images

Publications (1)

Publication Number Publication Date
IN2012DN02620A true IN2012DN02620A (en) 2015-09-04

Family

ID=41350612

Family Applications (1)

Application Number Title Priority Date Filing Date
IN2620DEN2012 IN2012DN02620A (en) 2009-09-30 2010-09-30

Country Status (8)

Country Link
US (1) US9251596B2 (en)
EP (1) EP2483863B1 (en)
JP (1) JP5695648B2 (en)
CN (1) CN102598054B (en)
ES (1) ES2595210T3 (en)
GB (1) GB0917154D0 (en)
IN (1) IN2012DN02620A (en)
WO (1) WO2011039515A1 (en)

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US9349186B2 (en) 2013-02-11 2016-05-24 General Electric Company Systems and methods for image segmentation using target image intensity
US9208572B2 (en) * 2013-09-20 2015-12-08 General Electric Company Systems and methods for image segmentation using a deformable atlas
US9818200B2 (en) * 2013-11-14 2017-11-14 Toshiba Medical Systems Corporation Apparatus and method for multi-atlas based segmentation of medical image data
WO2015109331A1 (en) * 2014-01-17 2015-07-23 The Johns Hopkins University Automated anatomical labeling by multi-contrast diffeomorphic probability fusion
US9483831B2 (en) * 2014-02-28 2016-11-01 International Business Machines Corporation Segmentation using hybrid discriminative generative label fusion of multiple atlases
US9449384B2 (en) 2014-04-30 2016-09-20 Mitsubishi Electric Research Laboratories, Inc. Method for registering deformable images using random Markov fields
US9964499B2 (en) * 2014-11-04 2018-05-08 Toshiba Medical Systems Corporation Method of, and apparatus for, material classification in multi-energy image data
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US10467767B2 (en) * 2016-12-23 2019-11-05 International Business Machines Corporation 3D segmentation reconstruction from 2D slices
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WO2018163499A1 (en) * 2017-03-10 2018-09-13 ソニー・オリンパスメディカルソリューションズ株式会社 Medical image display control device, medical image display device, medical information processing system, and medical image display control method
JP6785976B2 (en) * 2017-08-28 2020-11-18 富士フイルム株式会社 Brain image normalization device, method and program
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JP6998760B2 (en) * 2017-12-25 2022-01-18 浜松ホトニクス株式会社 Brain image analysis device, brain image analysis method, and brain image analysis program
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Also Published As

Publication number Publication date
JP2013506478A (en) 2013-02-28
WO2011039515A8 (en) 2012-05-18
ES2595210T3 (en) 2016-12-28
US9251596B2 (en) 2016-02-02
JP5695648B2 (en) 2015-04-08
EP2483863A1 (en) 2012-08-08
US20120281900A1 (en) 2012-11-08
GB0917154D0 (en) 2009-11-11
WO2011039515A1 (en) 2011-04-07
CN102598054A (en) 2012-07-18
EP2483863B1 (en) 2016-09-07
CN102598054B (en) 2016-02-10

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