CN114080646A - 信息处理装置、程序、学习完毕模型、诊断支援装置、学习装置及预测模型的生成方法 - Google Patents
信息处理装置、程序、学习完毕模型、诊断支援装置、学习装置及预测模型的生成方法 Download PDFInfo
- Publication number
- CN114080646A CN114080646A CN202080048846.6A CN202080048846A CN114080646A CN 114080646 A CN114080646 A CN 114080646A CN 202080048846 A CN202080048846 A CN 202080048846A CN 114080646 A CN114080646 A CN 114080646A
- Authority
- CN
- China
- Prior art keywords
- image data
- feature amount
- learning
- time point
- information
- 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
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
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B10/00—Instruments for taking body samples for diagnostic purposes; Other methods or instruments for diagnosis, e.g. for vaccination diagnosis, sex determination or ovulation-period determination; Throat striking implements
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
- A61B5/055—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
-
- 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]
-
- 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
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/25—Fusion techniques
- G06F18/253—Fusion techniques of extracted features
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- 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
- G06V10/80—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
- G06V10/806—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of extracted features
-
- 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
- G06V10/80—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
- G06V10/809—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of classification results, e.g. where the classifiers operate on the same input data
- G06V10/811—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of classification results, e.g. where the classifiers operate on the same input data the classifiers operating on different input data, e.g. multi-modal recognition
-
- 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
- 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
- G16H30/40—ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
-
- 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
-
- 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
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
-
- 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
- G06T2207/10081—Computed x-ray tomography [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
- 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
- G06T2207/20081—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
- G06T2207/20—Special algorithmic details
- G06T2207/20084—Artificial neural networks [ANN]
-
- 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
- G06T2207/20212—Image combination
- G06T2207/20221—Image fusion; Image merging
-
- 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
-
- 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
- G06T2207/30096—Tumor; Lesion
-
- 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)
- Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- General Health & Medical Sciences (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Public Health (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Biomedical Technology (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- General Physics & Mathematics (AREA)
- Evolutionary Computation (AREA)
- Databases & Information Systems (AREA)
- Radiology & Medical Imaging (AREA)
- Pathology (AREA)
- Data Mining & Analysis (AREA)
- Artificial Intelligence (AREA)
- Epidemiology (AREA)
- Primary Health Care (AREA)
- Computing Systems (AREA)
- Software Systems (AREA)
- Multimedia (AREA)
- Animal Behavior & Ethology (AREA)
- Veterinary Medicine (AREA)
- Surgery (AREA)
- Molecular Biology (AREA)
- Heart & Thoracic Surgery (AREA)
- Quality & Reliability (AREA)
- High Energy & Nuclear Physics (AREA)
- Biophysics (AREA)
- Business, Economics & Management (AREA)
- Evolutionary Biology (AREA)
- Human Resources & Organizations (AREA)
- General Engineering & Computer Science (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
Applications Claiming Priority (5)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2019137875 | 2019-07-26 | ||
| JP2019-137875 | 2019-07-26 | ||
| JP2020-036935 | 2020-03-04 | ||
| JP2020036935 | 2020-03-04 | ||
| PCT/JP2020/028074 WO2021020198A1 (ja) | 2019-07-26 | 2020-07-20 | 情報処理装置、プログラム、学習済みモデル、診断支援装置、学習装置及び予測モデルの生成方法 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114080646A true CN114080646A (zh) | 2022-02-22 |
Family
ID=74229630
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202080048846.6A Pending CN114080646A (zh) | 2019-07-26 | 2020-07-20 | 信息处理装置、程序、学习完毕模型、诊断支援装置、学习装置及预测模型的生成方法 |
Country Status (5)
| Country | Link |
|---|---|
| US (1) | US12169932B2 (https=) |
| EP (1) | EP4005498B1 (https=) |
| JP (1) | JP7170145B2 (https=) |
| CN (1) | CN114080646A (https=) |
| WO (1) | WO2021020198A1 (https=) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115187151A (zh) * | 2022-09-13 | 2022-10-14 | 北京锘崴信息科技有限公司 | 基于联邦学习的排放可信分析方法及金融信息评价方法 |
Families Citing this family (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI775161B (zh) * | 2020-09-28 | 2022-08-21 | 臺北醫學大學 | 腫瘤復發預測裝置與方法 |
| JPWO2022209290A1 (https=) * | 2021-03-30 | 2022-10-06 | ||
| US20240127948A1 (en) * | 2021-04-22 | 2024-04-18 | Sony Group Corporation | Patient monitoring system |
| CN113411236B (zh) * | 2021-06-23 | 2022-06-14 | 中移(杭州)信息技术有限公司 | 质差路由器检测方法、装置、设备及存储介质 |
| JPWO2023276977A1 (https=) * | 2021-06-28 | 2023-01-05 | ||
| WO2023276563A1 (ja) * | 2021-06-29 | 2023-01-05 | 大日本印刷株式会社 | 診断支援装置、コンピュータプログラム及び診断支援方法 |
| KR20230018929A (ko) * | 2021-07-30 | 2023-02-07 | 주식회사 루닛 | 환자에 대한 해석가능한 예측 결과를 생성하는 방법 및 시스템 |
| WO2023105976A1 (ja) * | 2021-12-08 | 2023-06-15 | 富士フイルム株式会社 | 臨床試験支援装置、臨床試験支援装置の作動方法、および臨床試験支援装置の作動プログラム |
| CN114398983B (zh) * | 2022-01-14 | 2024-11-05 | 腾讯科技(深圳)有限公司 | 分类预测方法、装置、设备、存储介质及计算机程序产品 |
| JP7779167B2 (ja) * | 2022-02-14 | 2025-12-03 | コニカミノルタ株式会社 | プログラム、動態解析システム及び動態解析装置 |
| CN115240854B (zh) * | 2022-07-29 | 2023-10-03 | 中国医学科学院北京协和医院 | 一种胰腺炎预后数据的处理方法及其系统 |
| KR20250073634A (ko) * | 2022-09-20 | 2025-05-27 | 각코우호우진 쥰텐도 | 신경변성 질환의 리스크 판정 방법 및 판정 장치 |
| CN115578347A (zh) * | 2022-10-12 | 2023-01-06 | 河北医科大学第二医院 | 基于深度学习对lhi脑水肿的定量分析方法、系统及设备 |
| CN115590481B (zh) * | 2022-12-15 | 2023-04-11 | 北京鹰瞳科技发展股份有限公司 | 一种用于预测认知障碍的装置和计算机可读存储介质 |
| WO2024209468A1 (en) * | 2023-04-03 | 2024-10-10 | Mor Research Applications Ltd. | Predicting onset and progression of neurodegenerative diseases using blood test data and machine learning models |
| KR102775338B1 (ko) * | 2023-05-25 | 2025-03-06 | (주)그래디언트 바이오컨버전스 | 유전자 정보 데이터와 뇌 이미지 데이터를 이용한 치매 진단 방법 및 시스템 |
| JP7554439B1 (ja) | 2023-05-30 | 2024-09-20 | メディカルリサーチ株式会社 | 情報処理方法、コンピュータプログラム及び情報処理装置 |
| WO2025177780A1 (ja) * | 2024-02-22 | 2025-08-28 | 国立大学法人大阪大学 | 認知機能予測システム |
| CN120833343B (zh) * | 2025-09-19 | 2025-12-30 | 季华实验室 | 液体体积预测方法、电子设备及计算机可读存储介质 |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS5773478A (en) | 1980-10-24 | 1982-05-08 | Toshiba Corp | Character recognition device |
| JP5113378B2 (ja) * | 2006-12-20 | 2013-01-09 | 富士フイルムRiファーマ株式会社 | 脳画像データに関する時系列データの解析方法、プログラムおよび記録媒体 |
| FR2931281B1 (fr) * | 2008-05-15 | 2014-07-18 | Univ Paris Curie | Procede et systeme automatise d'assistance au pronostic de la maladie d'alzheimer, et procede d'apprentissage d'un tel systeme |
| JP6384065B2 (ja) * | 2014-03-04 | 2018-09-05 | 日本電気株式会社 | 情報処理装置、学習方法、及び、プログラム |
| CN108604310B (zh) * | 2015-12-31 | 2022-07-26 | 威拓股份有限公司 | 用于使用神经网络架构来控制分配系统的方法、控制器和系统 |
| JP6355800B1 (ja) | 2017-06-28 | 2018-07-11 | ヤフー株式会社 | 学習装置、生成装置、学習方法、生成方法、学習プログラム、および生成プログラム |
| CA3078313A1 (en) * | 2017-10-31 | 2019-05-09 | Ge Healthcare Limited | Medical system for diagnosing cognitive disease pathology and/or outcome |
| WO2020255137A1 (en) * | 2019-06-19 | 2020-12-24 | Yissum Research Development Company Of The Hebrew University Of Jerusalem Ltd. | Machine learning-based anomaly detection |
| EP4088883A1 (en) * | 2021-05-11 | 2022-11-16 | Siemens Industry Software Ltd. | Method and system for predicting a collision free posture of a kinematic system |
-
2020
- 2020-07-20 EP EP20846460.2A patent/EP4005498B1/en active Active
- 2020-07-20 WO PCT/JP2020/028074 patent/WO2021020198A1/ja not_active Ceased
- 2020-07-20 CN CN202080048846.6A patent/CN114080646A/zh active Pending
- 2020-07-20 JP JP2021536958A patent/JP7170145B2/ja active Active
-
2021
- 2021-12-29 US US17/565,412 patent/US12169932B2/en active Active
Non-Patent Citations (2)
| Title |
|---|
| SIMEON SPASOV等: "A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer\'s disease", 《NEUROIMAGE》, vol. 189, 31 December 2019 (2019-12-31), pages 276 - 387 * |
| 程载和: "基于因素分解模型的两步人脸识别", 《计算机科学》, vol. 44, no. 11, 31 December 2017 (2017-12-31), pages 263 - 266 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115187151A (zh) * | 2022-09-13 | 2022-10-14 | 北京锘崴信息科技有限公司 | 基于联邦学习的排放可信分析方法及金融信息评价方法 |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2021020198A1 (ja) | 2021-02-04 |
| US12169932B2 (en) | 2024-12-17 |
| EP4005498A4 (en) | 2022-09-21 |
| JP7170145B2 (ja) | 2022-11-11 |
| EP4005498A1 (en) | 2022-06-01 |
| US20220122253A1 (en) | 2022-04-21 |
| EP4005498B1 (en) | 2025-07-23 |
| JPWO2021020198A1 (https=) | 2021-02-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP7170145B2 (ja) | 情報処理装置、プログラム、学習済みモデル、診断支援装置、学習装置及び予測モデルの生成方法 | |
| Xue et al. | AI-based differential diagnosis of dementia etiologies on multimodal data | |
| Odusami et al. | Explainable deep-learning-based diagnosis of Alzheimer’s disease using multimodal input fusion of PET and MRI images | |
| Li et al. | Alzheimer's disease diagnosis based on multiple cluster dense convolutional networks | |
| Tursynova et al. | Deep learning-enabled brain stroke classification on computed tomography images. | |
| Yun et al. | Flex-moe: Modeling arbitrary modality combination via the flexible mixture-of-experts | |
| Kumar et al. | Deep-learning-enabled multimodal data fusion for lung disease classification | |
| Sollee et al. | Artificial intelligence for medical image analysis in epilepsy | |
| JP7457292B2 (ja) | 脳画像解析装置、制御方法、及びプログラム | |
| Miao | Using machine learning algorithms to predict diabetes mellitus based on Pima Indians Diabetes dataset | |
| Li et al. | Ensemble of convolutional neural networks and multilayer perceptron for the diagnosis of mild cognitive impairment and Alzheimer's disease | |
| Park et al. | Deep joint learning of pathological region localization and Alzheimer’s disease diagnosis | |
| Jain et al. | A deep learning-based feature extraction model for classification brain tumor | |
| Khader et al. | Medical diagnosis with large scale multimodal transformers: Leveraging diverse data for more accurate diagnosis | |
| Lyu et al. | Learning neuroimaging models from health system-scale data | |
| Amador et al. | A multimodal multitask deep learning model for predicting stroke lesion and functional outcomes using 4D CTP imaging and clinical metadata | |
| Li et al. | LRNet: Link Residual Neural Network for Blood Vessel Segmentation in OCTA Images | |
| Brzus et al. | A clinical neuroimaging platform for rapid, automated lesion detection and personalized post-stroke outcome prediction | |
| Hasan et al. | A Novel Artificial Intelligence (AI) Method to Classify and Predict the Progression of Alzheimer’s Disease | |
| Gologorsky et al. | Generating novel pituitary datasets from open-source imaging data and deep volumetric segmentation | |
| Mudholkar et al. | Deep Transfer Learning for Schizophrenia Detection Using Brain MRI | |
| Thavasimuthu et al. | Classification of Alzheimer's Disease using Attention UNet-MobileNet Model | |
| TWI822460B (zh) | 罹患阿茲海默症之風險分析方法 | |
| Kaur et al. | Brain Region Segmentation for Alzheimer’s Disease Diagnosis: A Comprehensive Review | |
| Yao et al. | FC-Ensemble: An Ensemble Data Enhancement Method to Increase the Performance of Analysis the Staging of Alzheimer's Disease Based on Brain MRI |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |