RU2653108C2 - Интегрированное фенотипирование с использованием признаков текстуры изображения - Google Patents

Интегрированное фенотипирование с использованием признаков текстуры изображения Download PDF

Info

Publication number
RU2653108C2
RU2653108C2 RU2015124052A RU2015124052A RU2653108C2 RU 2653108 C2 RU2653108 C2 RU 2653108C2 RU 2015124052 A RU2015124052 A RU 2015124052A RU 2015124052 A RU2015124052 A RU 2015124052A RU 2653108 C2 RU2653108 C2 RU 2653108C2
Authority
RU
Russia
Prior art keywords
image
texture
features
interest
values
Prior art date
Application number
RU2015124052A
Other languages
English (en)
Russian (ru)
Other versions
RU2015124052A (ru
Inventor
Ниланджана БАНЕРДЖИ
Невенка ДИМИТРОВА
Винай ВАРАДАН
Ситхартхан КАМАЛАКАРАН
Анхель ЯНЕВСКИ
Саян МАЙТИ
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 RU2015124052A publication Critical patent/RU2015124052A/ru
Application granted granted Critical
Publication of RU2653108C2 publication Critical patent/RU2653108C2/ru

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/40—Analysis of texture
    • G06T7/41—Analysis of texture based on statistical description of texture
    • G06T7/45—Analysis of texture based on statistical description of texture using co-occurrence matrix computation
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • 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
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30068—Mammography; Breast

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Data Mining & Analysis (AREA)
  • General Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Computing Systems (AREA)
  • Evolutionary Computation (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Artificial Intelligence (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Evolutionary Biology (AREA)
  • Mathematical Physics (AREA)
  • Probability & Statistics with Applications (AREA)
  • Image Analysis (AREA)
  • Magnetic Resonance Imaging Apparatus (AREA)
  • Image Processing (AREA)
  • Apparatus Associated With Microorganisms And Enzymes (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
RU2015124052A 2012-11-20 2013-10-25 Интегрированное фенотипирование с использованием признаков текстуры изображения RU2653108C2 (ru)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US201261728441P 2012-11-20 2012-11-20
US61/728,441 2012-11-20
PCT/IB2013/059663 WO2014080305A2 (en) 2012-11-20 2013-10-25 Integrated phenotyping employing image texture features.

Publications (2)

Publication Number Publication Date
RU2015124052A RU2015124052A (ru) 2017-01-10
RU2653108C2 true RU2653108C2 (ru) 2018-05-07

Family

ID=49955416

Family Applications (1)

Application Number Title Priority Date Filing Date
RU2015124052A RU2653108C2 (ru) 2012-11-20 2013-10-25 Интегрированное фенотипирование с использованием признаков текстуры изображения

Country Status (7)

Country Link
US (1) US9552649B2 (enExample)
EP (1) EP2923336B1 (enExample)
JP (1) JP6321026B2 (enExample)
CN (1) CN104798105B (enExample)
BR (1) BR112015011289A2 (enExample)
RU (1) RU2653108C2 (enExample)
WO (1) WO2014080305A2 (enExample)

Families Citing this family (28)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2901340A2 (en) * 2012-12-20 2015-08-05 Siemens Aktiengesellschaft Determination of a probability indicator value
CN104217213B (zh) * 2014-08-20 2018-04-27 哈尔滨工程大学 一种基于对称性理论的医学图像多阶段分类方法
FR3025317B1 (fr) * 2014-08-26 2022-09-23 Imabiotech Methode de caracterisation d'un echantillon par imagerie par spectrometrie de masse
AU2015334840B2 (en) * 2014-10-24 2021-10-21 Innosign B.V. Assessment of TGF-beta cellular signaling pathway activity using mathematical modelling of target gene expression
CN105184300A (zh) * 2015-09-01 2015-12-23 中国矿业大学(北京) 一种基于图像lbp的煤岩识别方法
CN105354577A (zh) * 2015-10-26 2016-02-24 中国矿业大学(北京) 一种用于煤岩识别的b-cdtm纹理特征提取方法
US10215830B2 (en) 2015-12-16 2019-02-26 The United States Of America, As Represented By The Secretary, Department Of Health And Human Services Automated cancer detection using MRI
US10127660B2 (en) * 2015-12-30 2018-11-13 Case Western Reserve University Radiomic features on diagnostic magnetic resonance enterography
US10078895B2 (en) * 2015-12-30 2018-09-18 Case Western Reserve University Prediction of recurrence of non-small cell lung cancer with tumor infiltrating lymphocyte (TIL) graphs
US10898079B2 (en) * 2016-03-04 2021-01-26 University Of Manitoba Intravascular plaque detection in OCT images
CN106127672B (zh) * 2016-06-21 2019-03-12 南京信息工程大学 基于fpga的图像纹理特征提取算法
CN109690613B (zh) * 2016-09-16 2023-10-13 凯杰有限公司 邻近影响补偿
CN108241865B (zh) * 2016-12-26 2021-11-02 哈尔滨工业大学 基于超声图像的多尺度多子图肝纤维化多级量化分期方法
EP3351956B1 (de) * 2017-01-19 2022-03-16 Siemens Healthcare GmbH Verfahren zur klassifikation von mittels einer magnetresonanz- fingerprinting methode von einem untersuchungsobjekt erfassten magnetresonanz-messdaten
WO2018172990A1 (en) * 2017-03-24 2018-09-27 Pie Medical Imaging B.V. Method and system for assessing vessel obstruction based on machine learning
EP3451286B1 (de) * 2017-08-30 2019-08-28 Siemens Healthcare GmbH Verfahren zum segmentieren einer organstruktur eines untersuchungsobjekts in medizinischen bilddaten
CN107895139B (zh) * 2017-10-19 2021-09-21 金陵科技学院 一种基于多特征融合的sar图像目标识别方法
EP3486674A1 (en) * 2017-11-17 2019-05-22 Koninklijke Philips N.V. Artificial intelligence-enabled localization of anatomical landmarks
CN110135227B (zh) * 2018-02-09 2022-06-03 电子科技大学 一种基于机器学习的激光点云室外场景自动分割方法
CN108596275A (zh) * 2018-05-10 2018-09-28 句容沣润塑料制品有限公司 一种应用图像关联度的图像模糊分类方法
CN108665431A (zh) * 2018-05-16 2018-10-16 南京信息工程大学 基于k-均值聚类的分数阶图像纹理增强方法
FR3082650B1 (fr) * 2018-06-19 2021-08-27 Hera Mi Systeme et procede pour le traitement d'au moins une region polluante d'une image numerique d'un element expose a des rayons x
US10818015B2 (en) 2019-01-28 2020-10-27 Florida Analytical Imaging Solutions, LLC. Automatic region of interest selection in centrosome analysis
CN110909652B (zh) * 2019-11-16 2022-10-21 中国水利水电科学研究院 纹理特征优选的农作物种植结构月尺度动态提取方法
CN111260636B (zh) * 2020-01-19 2023-07-25 郑州大学 模型训练方法及设备、图像处理方法及设备以及介质
EP4042378A1 (en) * 2020-01-24 2022-08-17 St. Jude Medical, Cardiology Division, Inc. System and method for generating three dimensional geometric models of anatomical regions
CN112633082B (zh) * 2020-12-04 2023-08-18 西安理工大学 一种多特征融合杂草检测方法
JP7605711B2 (ja) * 2021-07-29 2024-12-24 株式会社日立製作所 画像識別システム及び画像識別方法

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020046198A1 (en) * 2000-06-19 2002-04-18 Ben Hitt Heuristic method of classification
US20080195322A1 (en) * 2007-02-12 2008-08-14 The Board Of Regents Of The University Of Texas System Quantification of the Effects of Perturbations on Biological Samples
US20110026798A1 (en) * 2008-02-19 2011-02-03 The Trustees Of The University Of Pennyslvania System and method for automated segmentation, characterization, and classification of possibly malignant lesions and stratification of malignant tumors

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5426684A (en) * 1993-11-15 1995-06-20 Eastman Kodak Company Technique for finding the histogram region of interest for improved tone scale reproduction of digital radiographic images
JP2873955B1 (ja) * 1998-01-23 1999-03-24 東京工業大学長 画像処理方法および装置
US7461048B2 (en) * 2003-07-21 2008-12-02 Aureon Laboratories, Inc. Systems and methods for treating, diagnosing and predicting the occurrence of a medical condition
EP2070045B1 (en) * 2006-09-22 2018-06-27 Koninklijke Philips N.V. Advanced computer-aided diagnosis of lung nodules
US8787633B2 (en) * 2007-01-16 2014-07-22 Purdue Research Foundation System and method of organism identification
GB0705223D0 (en) * 2007-03-19 2007-04-25 Univ Sussex Method, apparatus and computer program for analysing medical image data
WO2011008262A2 (en) * 2009-07-13 2011-01-20 H. Lee Moffitt Cancer Center & Research Institute Methods and apparatus for diagnosis and/or prognosis of cancer
CN102122356A (zh) * 2011-03-16 2011-07-13 中国人民解放军第二军医大学 计算机辅助判别胰腺癌超声内镜图像的方法
CN102509113B (zh) * 2011-11-08 2013-04-24 浙江大学 一种脑瘤mib-1指数范围检测方法

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020046198A1 (en) * 2000-06-19 2002-04-18 Ben Hitt Heuristic method of classification
US20080195322A1 (en) * 2007-02-12 2008-08-14 The Board Of Regents Of The University Of Texas System Quantification of the Effects of Perturbations on Biological Samples
US20110026798A1 (en) * 2008-02-19 2011-02-03 The Trustees Of The University Of Pennyslvania System and method for automated segmentation, characterization, and classification of possibly malignant lesions and stratification of malignant tumors

Also Published As

Publication number Publication date
RU2015124052A (ru) 2017-01-10
JP6321026B2 (ja) 2018-05-09
CN104798105A (zh) 2015-07-22
BR112015011289A2 (pt) 2017-07-11
WO2014080305A2 (en) 2014-05-30
CN104798105B (zh) 2019-06-07
WO2014080305A3 (en) 2014-07-24
EP2923336A2 (en) 2015-09-30
JP2016505289A (ja) 2016-02-25
EP2923336B1 (en) 2017-12-13
US9552649B2 (en) 2017-01-24
US20150310632A1 (en) 2015-10-29

Similar Documents

Publication Publication Date Title
RU2653108C2 (ru) Интегрированное фенотипирование с использованием признаков текстуры изображения
Shrestha et al. A systematic review on the use of artificial intelligence in gynecologic imaging–background, state of the art, and future directions
US10846367B2 (en) Predicting recurrence in early stage non-small cell lung cancer (NSCLC) with integrated radiomic and pathomic features
US11011265B2 (en) Predicting prostate cancer risk of progression with multiparametric magnetic resonance imaging using machine learning and peritumoral radiomics
US10575774B2 (en) Predicting immunotherapy response in non-small cell lung cancer with serial radiomics
Bi et al. Automatic detection and classification of regions of FDG uptake in whole-body PET-CT lymphoma studies
Hsieh et al. Quantitative glioma grading using transformed gray-scale invariant textures of MRI
Wang et al. Multilevel binomial logistic prediction model for malignant pulmonary nodules based on texture features of CT image
Gut et al. Benchmarking of deep architectures for segmentation of medical images
US9483822B2 (en) Co-occurrence of local anisotropic gradient orientations
Hasan et al. Automated screening of MRI brain scanning using grey level statistics
US20220138949A1 (en) System and Method for Tissue Classification Using Quantitative Image Analysis of Serial Scans
CN109191422B (zh) 基于常规ct图像的缺血性脑卒中早期检测系统和方法
US10055842B2 (en) Entropy-based radiogenomic descriptions on magnetic resonance imaging (MRI) for molecular characterization of breast cancer
CN117594200A (zh) 一种基于影像组学知识库的肿瘤影像辅助解读系统
US20250272831A1 (en) Automated methods for determining fibroglandular density on mammograms
Nanthagopal et al. A region-based segmentation of tumour from brain CT images using nonlinear support vector machine classifier
Chen et al. Breast density in MRI: an AI-based quantification and relationship to assessment in mammography
US20250037868A1 (en) Methods and Systems for Medical Prediction Using Collagen Fiber Architecture of Lesions
Hasan et al. MRI brain scan classification using novel 3-D statistical features
Retico et al. A voxel-based neural approach (VBNA) to identify lung nodules in the ANODE09 study
Cárdenas-Peña et al. Adaptive Bayesian label fusion using kernel-based similarity metrics in hippocampus segmentation
Suárez-Cuenca et al. Automated detection of pulmonary nodules in CT: False positive reduction by combining multiple classifiers
Sobecki et al. Feature extraction optimized for prostate lesion classification
JP2025064906A (ja) 類似する医用画像の提供