JP6214563B2 - 定量的ｔ１マッピングを用いた、リスクに晒されたエリアの自動化された検出 - Google Patents

定量的ｔ１マッピングを用いた、リスクに晒されたエリアの自動化された検出 Download PDF

Info

Publication number
JP6214563B2
JP6214563B2 JP2014553834A JP2014553834A JP6214563B2 JP 6214563 B2 JP6214563 B2 JP 6214563B2 JP 2014553834 A JP2014553834 A JP 2014553834A JP 2014553834 A JP2014553834 A JP 2014553834A JP 6214563 B2 JP6214563 B2 JP 6214563B2
Authority
JP
Japan
Prior art keywords
image
contrast
medical imaging
imaging system
tissue type
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.)
Expired - Fee Related
Application number
JP2014553834A
Other languages
English (en)
Japanese (ja)
Other versions
JP2015510412A (ja
Inventor
ラトコ フォイクト，トビーアス
ラトコ フォイクト，トビーアス
ヤーネ ヴィートホフ，アンドレア
ヤーネ ヴィートホフ，アンドレア
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.)
Koninklijke Philips NV
Original Assignee
Koninklijke Philips NV
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 Koninklijke Philips NV filed Critical Koninklijke Philips NV
Publication of JP2015510412A publication Critical patent/JP2015510412A/ja
Application granted granted Critical
Publication of JP6214563B2 publication Critical patent/JP6214563B2/ja
Expired - Fee Related legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

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
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques
    • G06F18/232—Non-hierarchical techniques
    • G06F18/2321—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T19/00—Manipulating three-dimensional [3D] models or images for computer graphics
    • G06T19/20—Editing of three-dimensional [3D] images, e.g. changing shapes or colours, aligning objects or positioning parts
    • 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
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/174—Segmentation; Edge detection involving the use of two or more images
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
    • G06T7/33—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based 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
    • G06T2207/10024—Color 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
    • G06T2207/10—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
    • G06T2207/10072—Tomographic images
    • G06T2207/10088—Magnetic resonance imaging [MRI]
    • G06T2207/10096—Dynamic contrast-enhanced magnetic resonance imaging [DCE-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
    • G06T2207/20076—Probabilistic image processing
    • 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
    • G06T2207/30048—Heart; Cardiac
    • 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
    • G06T2207/30101—Blood vessel; Artery; Vein; Vascular
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2210/00—Indexing scheme for image generation or computer graphics
    • G06T2210/41—Medical
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2219/00—Indexing scheme for manipulating 3D models or images for computer graphics
    • G06T2219/20—Indexing scheme for editing of 3D models
    • G06T2219/2012—Colour editing, changing, or manipulating; Use of colour codes

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Data Mining & Analysis (AREA)
  • General Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Radiology & Medical Imaging (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Medical Informatics (AREA)
  • General Health & Medical Sciences (AREA)
  • Quality & Reliability (AREA)
  • Computer Graphics (AREA)
  • Architecture (AREA)
  • Software Systems (AREA)
  • Computer Hardware Design (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Probability & Statistics with Applications (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Evolutionary Computation (AREA)
  • Magnetic Resonance Imaging Apparatus (AREA)
  • Apparatus For Radiation Diagnosis (AREA)
  • Image Analysis (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)
JP2014553834A 2012-01-27 2013-01-22 定量的ｔ１マッピングを用いた、リスクに晒されたエリアの自動化された検出 Expired - Fee Related JP6214563B2 (ja)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US201261591412P 2012-01-27 2012-01-27
US61/591,412 2012-01-27
PCT/IB2013/050543 WO2013111051A1 (en) 2012-01-27 2013-01-22 Automated detection of area at risk using quantitative t1 mapping

Publications (2)

Publication Number Publication Date
JP2015510412A JP2015510412A (ja) 2015-04-09
JP6214563B2 true JP6214563B2 (ja) 2017-10-18

Family

ID=47747731

Family Applications (1)

Application Number Title Priority Date Filing Date
JP2014553834A Expired - Fee Related JP6214563B2 (ja) 2012-01-27 2013-01-22 定量的ｔ１マッピングを用いた、リスクに晒されたエリアの自動化された検出

Country Status (7)

Country Link
US (1) US9547942B2 (enExample)
EP (1) EP2807633B1 (enExample)
JP (1) JP6214563B2 (enExample)
CN (1) CN104094314B (enExample)
BR (1) BR112014018076A8 (enExample)
RU (1) RU2626869C2 (enExample)
WO (1) WO2013111051A1 (enExample)

Families Citing this family (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP6132653B2 (ja) * 2013-05-08 2017-05-24 東芝メディカルシステムズ株式会社 画像処理装置及び磁気共鳴イメージング装置
WO2015069824A2 (en) * 2013-11-06 2015-05-14 Lehigh University Diagnostic system and method for biological tissue analysis
CN104881865B (zh) * 2015-04-29 2017-11-24 北京林业大学 基于无人机图像分析的森林病虫害监测预警方法及其系统
US10466326B2 (en) * 2015-05-15 2019-11-05 Stc. Unm Quantitative [Fe]-MRI (femri) of anti-PSMA-conjugated SPIONs based on PSMA expression levels
EP3341890B1 (en) * 2015-08-25 2021-04-28 Koninklijke Philips N.V. Tissue microarray analysis
JP6326034B2 (ja) * 2015-12-11 2018-05-16 安西メディカル株式会社 キセノンｃｔ装置
WO2017134830A1 (ja) * 2016-02-05 2017-08-10 株式会社日立製作所 医用画像診断支援装置、および、磁気共鳴イメージング装置
US10695134B2 (en) 2016-08-25 2020-06-30 Verily Life Sciences Llc Motion execution of a robotic system
EP3373247A1 (en) * 2017-03-09 2018-09-12 Koninklijke Philips N.V. Image segmentation and prediction of segmentation
EP3379281A1 (en) * 2017-03-20 2018-09-26 Koninklijke Philips N.V. Image segmentation using reference gray scale values
EP3477324B1 (en) * 2017-10-31 2025-03-26 Pie Medical Imaging BV Improving left ventricle segmentation in contrast-enhanced cine mri datasets
US11344374B2 (en) * 2018-08-13 2022-05-31 Verily Life Sciences Llc Detection of unintentional movement of a user interface device
TWI758950B (zh) * 2020-11-13 2022-03-21 大陸商昆山瑞創芯電子有限公司 應用於顯示面板的校準方法及校準裝置
CN118022200A (zh) * 2022-11-11 2024-05-14 中硼(厦门)医疗器械有限公司 治疗计划系统、重叠自动检查方法及治疗计划的制定方法
US12561873B2 (en) 2023-02-20 2026-02-24 Canon Medical Systems Corporation Image processing apparatus and method
CN118733837B (zh) * 2024-06-04 2025-01-14 陕西盛世鹏展智能科技有限公司 一种基于大数据的物联网设备控制系统及方法

Family Cites Families (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS60165945A (ja) * 1984-02-10 1985-08-29 株式会社日立製作所 画像処理方式
KR20010012914A (ko) * 1997-05-23 2001-02-26 캐롤리나 하트 인스티튜트 전자기적 화상화 및 치료 시스템
US6205349B1 (en) 1998-09-29 2001-03-20 Siemens Medical Systems, Inc. Differentiating normal living myocardial tissue, injured living myocardial tissue, and infarcted myocardial tissue in vivo using magnetic resonance imaging
US6842638B1 (en) * 2001-11-13 2005-01-11 Koninklijke Philips Electronics N.V. Angiography method and apparatus
US20040218794A1 (en) * 2003-05-01 2004-11-04 Yi-Hsuan Kao Method for processing perfusion images
US7480412B2 (en) * 2003-12-16 2009-01-20 Siemens Medical Solutions Usa, Inc. Toboggan-based shape characterization
WO2007107931A2 (en) 2006-03-17 2007-09-27 Koninklijke Philips Electronics N.V. Combining magnetic resonance images
US10098563B2 (en) 2006-11-22 2018-10-16 Toshiba Medical Systems Corporation Magnetic resonance imaging apparatus
US8086297B2 (en) 2007-01-31 2011-12-27 Duke University Dark blood delayed enhancement magnetic resonance viability imaging techniques for assessing subendocardial infarcts
US9395431B2 (en) * 2008-05-01 2016-07-19 Sunnybrook Health Sciences Center Multi-contrast delayed enhancement cardiac magnetic resonance imaging
CN101916443B (zh) * 2010-08-19 2012-10-17 中国科学院深圳先进技术研究院 Ct图像的处理方法及系统
CN102004917B (zh) * 2010-12-17 2012-04-18 南方医科大学 一种图像边缘近邻描述特征算子的提取方法

Also Published As

Publication number Publication date
WO2013111051A1 (en) 2013-08-01
CN104094314B (zh) 2018-06-08
EP2807633B1 (en) 2018-08-22
CN104094314A (zh) 2014-10-08
RU2626869C2 (ru) 2017-08-02
EP2807633A1 (en) 2014-12-03
US9547942B2 (en) 2017-01-17
US20150213652A1 (en) 2015-07-30
RU2014134899A (ru) 2016-03-20
JP2015510412A (ja) 2015-04-09
BR112014018076A8 (pt) 2017-07-11
BR112014018076A2 (enExample) 2017-06-20

Similar Documents

Publication Publication Date Title
EP2807633B1 (en) Automated detection of area at risk using quantitative t1 mapping
US9424644B2 (en) Methods and systems for evaluating bone lesions
Yu et al. Automated radiation targeting in head-and-neck cancer using region-based texture analysis of PET and CT images
JP6595729B2 (ja) 医療画像における変化検出
US9147242B2 (en) Processing system for medical scan images
EP2407927A1 (en) A method and device for evaluating evolution of tumoral lesions
JP2019088777A (ja) 造影シネｍｒｉデータセットにおける左心室のセグメント分割の改善
JP2017520305A (ja) 急性脳虚血患者における組織領域の区分法及び予測法
WO2019007952A1 (en) METHOD OF EVALUATING IMAGE ANALYSIS OF PROBABILITY THAT ISCHEMIA IN A CEREBRAL TISSUE AREA RESULTS IN INFARCTION OF THIS BRAIN TISSUE AREA
Sun et al. Automated template-based PET region of interest analyses in the aging brain
Yang et al. Delineation of FDG-PET tumors from heterogeneous background using spectral clustering
Elnakib et al. New automated Markov–Gibbs random field based framework for myocardial wall viability quantification on agent enhanced cardiac magnetic resonance images
US20110194741A1 (en) Brain ventricle analysis
CN110383347A (zh) 皮质畸形识别
Shen et al. An improved lesion detection approach based on similarity measurement between fuzzy intensity segmentation and spatial probability maps
WO2017198518A1 (en) Image data processing device
Goyal et al. Development of a Stand‐Alone Independent Graphical User Interface for Neurological Disease Prediction with Automated Extraction and Segmentation of Gray and White Matter in Brain MRI Images
Slomka et al. Quantification of myocardial perfusion
Johnstone et al. Assessment of tissue edema in patients with acute myocardial infarction by computer‐assisted quantification of triple inversion recovery prepared MRI of the myocardium
Wesarg AHA conform analysis of myocardial function using and extending the toolkits ITK and VTK
O'Brien et al. Machine Learning Based Cardiac Scar Detection in Computed Tomography
WO2025136816A1 (en) Machine learning enabled analysis of medical imaging data for assessment of disease progression and treatment response
Madhav et al. An Automated Segmentation Method for Assesing Myocardial Infarct Size Using K-Means Algorithm
Urbán et al. Semi-automatic tumor contouring method using PET and MRI medical images
Levy 16.4 Biomedical Informatics Systems to Support Treatment Response

Legal Events

Date Code Title Description
A621 Written request for application examination

Free format text: JAPANESE INTERMEDIATE CODE: A621

Effective date: 20160119

A977 Report on retrieval

Free format text: JAPANESE INTERMEDIATE CODE: A971007

Effective date: 20161117

A131 Notification of reasons for refusal

Free format text: JAPANESE INTERMEDIATE CODE: A131

Effective date: 20170104

A601 Written request for extension of time

Free format text: JAPANESE INTERMEDIATE CODE: A601

Effective date: 20170328

A521 Request for written amendment filed

Free format text: JAPANESE INTERMEDIATE CODE: A523

Effective date: 20170424

A131 Notification of reasons for refusal

Free format text: JAPANESE INTERMEDIATE CODE: A131

Effective date: 20170516

A521 Request for written amendment filed

Free format text: JAPANESE INTERMEDIATE CODE: A523

Effective date: 20170803

TRDD Decision of grant or rejection written
A01 Written decision to grant a patent or to grant a registration (utility model)

Free format text: JAPANESE INTERMEDIATE CODE: A01

Effective date: 20170822

A61 First payment of annual fees (during grant procedure)

Free format text: JAPANESE INTERMEDIATE CODE: A61

Effective date: 20170919

R150 Certificate of patent or registration of utility model

Ref document number: 6214563

Country of ref document: JP

Free format text: JAPANESE INTERMEDIATE CODE: R150

R250 Receipt of annual fees

Free format text: JAPANESE INTERMEDIATE CODE: R250

R250 Receipt of annual fees

Free format text: JAPANESE INTERMEDIATE CODE: R250

R250 Receipt of annual fees

Free format text: JAPANESE INTERMEDIATE CODE: R250

LAPS Cancellation because of no payment of annual fees