RU2017116859A - Классификация состояния исследуемой ткани на основании лонгитудинальных признаков - Google Patents

Классификация состояния исследуемой ткани на основании лонгитудинальных признаков Download PDF

Info

Publication number
RU2017116859A
RU2017116859A RU2017116859A RU2017116859A RU2017116859A RU 2017116859 A RU2017116859 A RU 2017116859A RU 2017116859 A RU2017116859 A RU 2017116859A RU 2017116859 A RU2017116859 A RU 2017116859A RU 2017116859 A RU2017116859 A RU 2017116859A
Authority
RU
Russia
Prior art keywords
images
tissue
processor
under study
pair
Prior art date
Application number
RU2017116859A
Other languages
English (en)
Russian (ru)
Inventor
Лилла БОРОЦКИ
Рафаэль ВИМКЕР
Original Assignee
Конинклейке Филипс Н.В.
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 Конинклейке Филипс Н.В. filed Critical Конинклейке Филипс Н.В.
Publication of RU2017116859A publication Critical patent/RU2017116859A/ru

Links

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/02—Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
    • A61B6/03—Computed tomography [CT]
    • A61B6/032—Transmission computed tomography [CT]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0033—Features or image-related aspects of imaging apparatus, e.g. for MRI, optical tomography or impedance tomography apparatus; Arrangements of imaging apparatus in a room
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0033—Features or image-related aspects of imaging apparatus, e.g. for MRI, optical tomography or impedance tomography apparatus; Arrangements of imaging apparatus in a room
    • A61B5/0035—Features or image-related aspects of imaging apparatus, e.g. for MRI, optical tomography or impedance tomography apparatus; Arrangements of imaging apparatus in a room adapted for acquisition of images from more than one imaging mode, e.g. combining MRI and optical tomography
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/02—Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
    • A61B6/03—Computed tomography [CT]
    • A61B6/037—Emission tomography
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
    • A61B6/5211—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data
    • A61B6/5217—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data extracting a diagnostic or physiological parameter from medical diagnostic data
    • 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
    • G06T7/0014—Biomedical image inspection using an image reference approach
    • 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
    • G06T7/0014—Biomedical image inspection using an image reference approach
    • G06T7/0016—Biomedical image inspection using an image reference approach involving temporal comparison
    • 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
    • G16H30/20—ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
    • 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
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • A61B5/7267—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271—Specific aspects of physiological measurement analysis
    • A61B5/7275—Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/74—Details of notification to user or communication with user or patient; User input means
    • A61B5/7475—User input or interface means, e.g. keyboard, pointing device, joystick
    • A61B5/748—Selection of a region of interest, e.g. using a graphics tablet
    • A61B5/7485—Automatic selection of region of interest
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
    • A61B6/5211—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data
    • A61B6/5229—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data combining image data of a patient, e.g. combining a functional image with an anatomical image
    • A61B6/5235—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data combining image data of a patient, e.g. combining a functional image with an anatomical image combining images from the same or different ionising radiation imaging techniques, e.g. PET and CT
    • 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
    • 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
    • G06T2207/10132—Ultrasound image
    • 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
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing

Landscapes

  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Medical Informatics (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Biomedical Technology (AREA)
  • Physics & Mathematics (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Pathology (AREA)
  • Radiology & Medical Imaging (AREA)
  • Veterinary Medicine (AREA)
  • Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • Molecular Biology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Biophysics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • High Energy & Nuclear Physics (AREA)
  • Optics & Photonics (AREA)
  • Theoretical Computer Science (AREA)
  • Physiology (AREA)
  • Quality & Reliability (AREA)
  • General Physics & Mathematics (AREA)
  • Primary Health Care (AREA)
  • Epidemiology (AREA)
  • Pulmonology (AREA)
  • Databases & Information Systems (AREA)
  • Data Mining & Analysis (AREA)
  • Artificial Intelligence (AREA)
  • Psychiatry (AREA)
  • Signal Processing (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)
  • Apparatus For Radiation Diagnosis (AREA)
  • Image Analysis (AREA)
RU2017116859A 2014-10-13 2015-09-29 Классификация состояния исследуемой ткани на основании лонгитудинальных признаков RU2017116859A (ru)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US201462062977P 2014-10-13 2014-10-13
US62/062,977 2014-10-13
PCT/IB2015/057433 WO2016059493A1 (en) 2014-10-13 2015-09-29 Classification of a health state of tissue of interest based on longitudinal features

Publications (1)

Publication Number Publication Date
RU2017116859A true RU2017116859A (ru) 2018-11-15

Family

ID=54292866

Family Applications (1)

Application Number Title Priority Date Filing Date
RU2017116859A RU2017116859A (ru) 2014-10-13 2015-09-29 Классификация состояния исследуемой ткани на основании лонгитудинальных признаков

Country Status (7)

Country Link
US (2) US10219767B2 (enExample)
EP (1) EP3206565A1 (enExample)
JP (1) JP6865678B2 (enExample)
CN (1) CN107072613B (enExample)
BR (1) BR112017007383A2 (enExample)
RU (1) RU2017116859A (enExample)
WO (1) WO2016059493A1 (enExample)

Families Citing this family (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3410393A1 (en) * 2017-06-01 2018-12-05 Siemens Healthcare GmbH Comparing medical images
GB201716890D0 (en) * 2017-10-13 2017-11-29 Optellum Ltd System, method and apparatus for assisting a determination of medical images
US11625597B2 (en) * 2017-11-15 2023-04-11 Canon Medical Systems Corporation Matching network for medical image analysis
CN109376419B (zh) * 2018-10-16 2023-12-22 北京字节跳动网络技术有限公司 一种数据模型的生成方法、装置、电子设备及可读介质
US10811135B2 (en) * 2018-12-27 2020-10-20 General Electric Company Systems and methods to determine disease progression from artificial intelligence detection output
DE102019211536A1 (de) * 2019-08-01 2021-02-04 Siemens Healthcare Gmbh Automatische Lokalisierung einer Struktur
CN111784705B (zh) * 2020-06-24 2024-04-02 上海联影医疗科技股份有限公司 感兴趣区域的勾画方法、装置、设备和存储介质
CN112472346B (zh) * 2020-11-26 2021-12-24 南通市第二人民医院 一种基于大数据的牙龈保护方法和装置
US12315160B2 (en) * 2022-03-16 2025-05-27 Optellum Limited Method and apparatus to predict feature state change within an image

Family Cites Families (22)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6466687B1 (en) 1997-02-12 2002-10-15 The University Of Iowa Research Foundation Method and apparatus for analyzing CT images to determine the presence of pulmonary tissue pathology
US7211247B2 (en) 2001-04-09 2007-05-01 University Of Southern California Lentivirus vectors for gene transfer to alveolar epithelial cells
US6992280B2 (en) * 2002-04-04 2006-01-31 Synarc, Inc. Test object for calibration of imaging measurements of mammalian skeletal joints
US7418123B2 (en) * 2002-07-12 2008-08-26 University Of Chicago Automated method and system for computerized image analysis for prognosis
US20040122708A1 (en) * 2002-12-18 2004-06-24 Avinash Gopal B. Medical data analysis method and apparatus incorporating in vitro test data
US7912528B2 (en) * 2003-06-25 2011-03-22 Siemens Medical Solutions Usa, Inc. Systems and methods for automated diagnosis and decision support for heart related diseases and conditions
WO2005079306A2 (en) 2004-02-13 2005-09-01 University Of Chicago Method, system, and computer software product for feature-based correlation of lesions from multiple images
CN100435736C (zh) * 2006-12-13 2008-11-26 林井副 基于多层螺旋ct的人体索条状组织同层显示成像方法
KR20090098842A (ko) * 2006-12-29 2009-09-17 코닌클리케 필립스 일렉트로닉스 엔.브이. 이미지 유도 중재 시술에서 수술중 움직임을 보상하는 개선된 이미지 정합 및 방법
US8442285B2 (en) 2007-04-02 2013-05-14 The Trustees Of The University Of Pennsylvania Combined feature ensemble mutual information image registration
US8295575B2 (en) 2007-10-29 2012-10-23 The Trustees of the University of PA. Computer assisted diagnosis (CAD) of cancer using multi-functional, multi-modal in-vivo magnetic resonance spectroscopy (MRS) and imaging (MRI)
EP2344982A4 (en) * 2008-10-10 2012-09-19 Sti Medical Systems Llc METHOD FOR TISSUE CLASSIFICATION IN CERVICAL IMAGING
EP2338121A1 (en) 2008-10-10 2011-06-29 Koninklijke Philips Electronics N.V. Health-risk metric determination and/or presentation
US9526429B2 (en) * 2009-02-06 2016-12-27 Resmed Sensor Technologies Limited Apparatus, system and method for chronic disease monitoring
WO2010115885A1 (en) 2009-04-03 2010-10-14 Oslo Universitetssykehus Hf Predictive classifier score for cancer patient outcome
EP2441052B1 (en) * 2009-06-10 2013-01-23 Koninklijke Philips Electronics N.V. Visualization apparatus for visualizing an image data set
US20110129129A1 (en) * 2009-11-30 2011-06-02 General Electric Company System and method for integrated quantifiable detection, diagnosis and monitoring of disease using population related data for determining a disease signature
WO2011139362A1 (en) * 2010-05-03 2011-11-10 Sti Medical Systems, Llc Image analysis for cervical neoplasia detection and diagnosis
US10267882B2 (en) * 2010-10-13 2019-04-23 Toshiba Medical Systems Corporation MRI T1 image-guided tissue diagnostics
WO2013142706A1 (en) 2012-03-21 2013-09-26 The Johns Hopkins University A method of analyzing multi-sequence mri data for analysing brain abnormalities in a subject
JP6017284B2 (ja) * 2012-11-30 2016-10-26 東芝メディカルシステムズ株式会社 医用画像診断装置
CN104885126B (zh) * 2012-12-27 2018-01-05 皇家飞利浦有限公司 感兴趣组织的计算机辅助识别

Also Published As

Publication number Publication date
US10219767B2 (en) 2019-03-05
CN107072613B (zh) 2021-02-26
JP6865678B2 (ja) 2021-04-28
BR112017007383A2 (pt) 2018-01-16
WO2016059493A1 (en) 2016-04-21
US20180220985A1 (en) 2018-08-09
CN107072613A (zh) 2017-08-18
JP2017532998A (ja) 2017-11-09
US20190150870A1 (en) 2019-05-23
EP3206565A1 (en) 2017-08-23

Similar Documents

Publication Publication Date Title
CA2905637C (en) Systems, methods, and computer-readable media for identifying when a subject is likely to be affected by a medical condition
Li et al. The secrets of salient object segmentation
US10762630B2 (en) System and method for structures detection and multi-class image categorization in medical imaging
CN104951799B (zh) 一种sar遥感影像溢油检测识别方法
JP4947589B2 (ja) 類似画像検索装置
CN104394771B (zh) 超声图像处理
US20130231552A1 (en) Method and System for Diagnosis of Attention Deficit Hyperactivity Disorder from Magnetic Resonance Images
JP2017532998A5 (enExample)
RU2017110538A (ru) Системы и способы сегментации медицинских изображений на основании признаков, основанных на анатомических ориентирах
RU2017142112A (ru) Устройство и способ персонализированного поиска на основе признаков изображения продукта
RU2016148690A (ru) Способ и система компьютерной стратификации пациентов на основе сложности случаев заболеваний
Hobson et al. Classifying anti-nuclear antibodies HEp-2 images: A benchmarking platform
RU2012103474A (ru) Система визуализации для оптимального определения стадии рака, основанная на правилах поддержки принятия решений и индивидуальном подходе к пациенту
Casanova et al. Texture analysis using fractal descriptors estimated by the mutual interference of color channels
Török et al. Digital image analysis with fully connected convolutional neural network to facilitate hysteroscopic fibroid resection
TW202228150A (zh) 情緒指標預測方法與系統
WO2010035518A1 (ja) 医用画像処理装置及びプログラム
Gardezi et al. Fusion of completed local binary pattern features with curvelet features for mammogram classification
CN112215217B (zh) 模拟医师阅片的数字图像识别方法及装置
CN105809181A (zh) 用于Logo检测的方法和设备
Muhimmah et al. Analysis of features to distinguish epithelial cells and inflammatory cells in Pap smear images
Tang et al. Splat feature classification: Detection of the presence of large retinal hemorrhages
CN114742763B (zh) 骨骼图像的识别优化方法、系统、存储介质及电子设备
JP4925111B2 (ja) 類似画像検索装置
CN103679198B (zh) 一种基于k近邻的视网膜内节/外节缺失自动检测方法