JP7325411B2 - 心エコー図を分析する方法及び装置 - Google Patents
心エコー図を分析する方法及び装置 Download PDFInfo
- Publication number
- JP7325411B2 JP7325411B2 JP2020524199A JP2020524199A JP7325411B2 JP 7325411 B2 JP7325411 B2 JP 7325411B2 JP 2020524199 A JP2020524199 A JP 2020524199A JP 2020524199 A JP2020524199 A JP 2020524199A JP 7325411 B2 JP7325411 B2 JP 7325411B2
- Authority
- JP
- Japan
- Prior art keywords
- echocardiograms
- echocardiogram
- pair
- consecutive
- computer
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims description 55
- 230000008859 change Effects 0.000 claims description 27
- 230000000747 cardiac effect Effects 0.000 claims description 16
- 238000013135 deep learning Methods 0.000 claims description 14
- 230000009467 reduction Effects 0.000 claims description 12
- 238000012549 training Methods 0.000 claims description 6
- 230000004217 heart function Effects 0.000 claims description 5
- 239000013598 vector Substances 0.000 claims description 5
- 230000015654 memory Effects 0.000 description 18
- 238000004458 analytical method Methods 0.000 description 11
- 238000004891 communication Methods 0.000 description 6
- 230000006870 function Effects 0.000 description 6
- 238000010586 diagram Methods 0.000 description 5
- 210000005240 left ventricle Anatomy 0.000 description 5
- 238000002592 echocardiography Methods 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 230000002861 ventricular Effects 0.000 description 4
- 238000004590 computer program Methods 0.000 description 3
- 235000019800 disodium phosphate Nutrition 0.000 description 3
- 238000005259 measurement Methods 0.000 description 3
- 238000013527 convolutional neural network Methods 0.000 description 2
- 238000003384 imaging method Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 206010002329 Aneurysm Diseases 0.000 description 1
- 208000031229 Cardiomyopathies Diseases 0.000 description 1
- 208000002330 Congenital Heart Defects Diseases 0.000 description 1
- 206010028980 Neoplasm Diseases 0.000 description 1
- 208000001910 Ventricular Heart Septal Defects Diseases 0.000 description 1
- 210000001015 abdomen Anatomy 0.000 description 1
- 230000005856 abnormality Effects 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000017531 blood circulation Effects 0.000 description 1
- 210000004204 blood vessel Anatomy 0.000 description 1
- 210000005242 cardiac chamber Anatomy 0.000 description 1
- 208000028831 congenital heart disease Diseases 0.000 description 1
- 230000001186 cumulative effect Effects 0.000 description 1
- 238000013136 deep learning model Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 230000003205 diastolic effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000001605 fetal effect Effects 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 210000000232 gallbladder Anatomy 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 210000004185 liver Anatomy 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 210000004165 myocardium Anatomy 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 210000000056 organ Anatomy 0.000 description 1
- 230000001575 pathological effect Effects 0.000 description 1
- 210000000664 rectum Anatomy 0.000 description 1
- 238000009877 rendering Methods 0.000 description 1
- 238000012552 review Methods 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
- 230000001131 transforming effect Effects 0.000 description 1
- 238000002604 ultrasonography Methods 0.000 description 1
- 201000003130 ventricular septal defect Diseases 0.000 description 1
Images
Classifications
-
- 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
-
- 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
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
-
- 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
- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2560/00—Constructional details of operational features of apparatus; Accessories for medical measuring apparatus
- A61B2560/02—Operational features
Landscapes
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Public Health (AREA)
- Medical Informatics (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Epidemiology (AREA)
- Biomedical Technology (AREA)
- Life Sciences & Earth Sciences (AREA)
- Artificial Intelligence (AREA)
- Pathology (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- Radiology & Medical Imaging (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Databases & Information Systems (AREA)
- Biophysics (AREA)
- Veterinary Medicine (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- Molecular Biology (AREA)
- Heart & Thoracic Surgery (AREA)
- Evolutionary Computation (AREA)
- Fuzzy Systems (AREA)
- Mathematical Physics (AREA)
- Signal Processing (AREA)
- Psychiatry (AREA)
- Physiology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Ultra Sonic Daignosis Equipment (AREA)
- Image Analysis (AREA)
- Cardiology (AREA)
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US201762580491P | 2017-11-02 | 2017-11-02 | |
| US62/580,491 | 2017-11-02 | ||
| PCT/EP2018/079963 WO2019086586A1 (en) | 2017-11-02 | 2018-11-02 | A method and apparatus for analysing echocardiograms |
Publications (3)
| Publication Number | Publication Date |
|---|---|
| JP2021501633A JP2021501633A (ja) | 2021-01-21 |
| JP2021501633A5 JP2021501633A5 (https=) | 2021-12-09 |
| JP7325411B2 true JP7325411B2 (ja) | 2023-08-14 |
Family
ID=64270837
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2020524199A Active JP7325411B2 (ja) | 2017-11-02 | 2018-11-02 | 心エコー図を分析する方法及び装置 |
Country Status (5)
| Country | Link |
|---|---|
| US (1) | US20210219922A1 (https=) |
| EP (1) | EP3704707B1 (https=) |
| JP (1) | JP7325411B2 (https=) |
| CN (1) | CN111448614B (https=) |
| WO (1) | WO2019086586A1 (https=) |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11446009B2 (en) * | 2018-12-11 | 2022-09-20 | Eko.Ai Pte. Ltd. | Clinical workflow to diagnose heart disease based on cardiac biomarker measurements and AI recognition of 2D and doppler modality echocardiogram images |
| US11931207B2 (en) * | 2018-12-11 | 2024-03-19 | Eko.Ai Pte. Ltd. | Artificial intelligence (AI) recognition of echocardiogram images to enhance a mobile ultrasound device |
| US11301996B2 (en) * | 2018-12-11 | 2022-04-12 | Eko.Ai Pte. Ltd. | Training neural networks of an automatic clinical workflow that recognizes and analyzes 2D and doppler modality echocardiogram images |
| US12322100B2 (en) * | 2018-12-11 | 2025-06-03 | Eko.Ai Pte. Ltd. | Automatic clinical workflow that recognizes and analyzes 2D and doppler modality echocardiogram images for automated cardiac measurements and grading of aortic stenosis severity |
| US12400762B2 (en) * | 2018-12-11 | 2025-08-26 | Eko.Ai Pte. Ltd. | Automatic clinical workflow that recognizes and analyzes 2D and doppler modality echocardiogram images for automated cardiac measurements and diagnosis of cardiac amyloidosis and hypertrophic cardiomyopathy |
| US12001939B2 (en) * | 2018-12-11 | 2024-06-04 | Eko.Ai Pte. Ltd. | Artificial intelligence (AI)-based guidance for an ultrasound device to improve capture of echo image views |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007526016A (ja) | 2003-06-25 | 2007-09-13 | シーメンス メディカル ソリューションズ ユーエスエー インコーポレイテッド | 心撮像の自動局所心筋評価を行うシステム及び方法 |
| JP2012139487A (ja) | 2010-12-13 | 2012-07-26 | Toshiba Corp | 超音波診断装置、画像処理装置及び画像処理方法 |
| WO2016194161A1 (ja) | 2015-06-03 | 2016-12-08 | 株式会社日立製作所 | 超音波診断装置、及び画像処理方法 |
| WO2017056078A1 (en) | 2015-10-02 | 2017-04-06 | Koninklijke Philips N.V. | System for mapping findings to pertinent echocardiogram loops |
| JP2017068838A (ja) | 2015-09-29 | 2017-04-06 | パナソニックＩｐマネジメント株式会社 | 情報端末の制御方法及びプログラム |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5911133A (en) * | 1997-10-22 | 1999-06-08 | Rush-Presbyterian -St. Luke's Medical Center | User interface for echocardiographic report generation |
| US6447450B1 (en) * | 1999-11-02 | 2002-09-10 | Ge Medical Systems Global Technology Company, Llc | ECG gated ultrasonic image compounding |
| CN1725978A (zh) * | 2002-12-13 | 2006-01-25 | 皇家飞利浦电子股份有限公司 | 用于处理一系列表示心动周期的图像帧的系统和方法 |
| WO2016038535A1 (en) * | 2014-09-10 | 2016-03-17 | Koninklijke Philips N.V. | Image report annotation identification |
| CN106846306A (zh) * | 2017-01-13 | 2017-06-13 | 重庆邮电大学 | 一种超声图像自动描述方法和系统 |
| EP3625763B1 (en) * | 2017-05-18 | 2024-09-04 | Koninklijke Philips N.V. | Convolutional deep learning analysis of temporal cardiac images |
| CN107184198A (zh) * | 2017-06-01 | 2017-09-22 | 广州城市职业学院 | 一种心电信号分类识别方法 |
-
2018
- 2018-11-02 CN CN201880078066.9A patent/CN111448614B/zh active Active
- 2018-11-02 US US16/760,678 patent/US20210219922A1/en active Pending
- 2018-11-02 WO PCT/EP2018/079963 patent/WO2019086586A1/en not_active Ceased
- 2018-11-02 EP EP18800551.6A patent/EP3704707B1/en active Active
- 2018-11-02 JP JP2020524199A patent/JP7325411B2/ja active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007526016A (ja) | 2003-06-25 | 2007-09-13 | シーメンス メディカル ソリューションズ ユーエスエー インコーポレイテッド | 心撮像の自動局所心筋評価を行うシステム及び方法 |
| JP2012139487A (ja) | 2010-12-13 | 2012-07-26 | Toshiba Corp | 超音波診断装置、画像処理装置及び画像処理方法 |
| WO2016194161A1 (ja) | 2015-06-03 | 2016-12-08 | 株式会社日立製作所 | 超音波診断装置、及び画像処理方法 |
| JP2017068838A (ja) | 2015-09-29 | 2017-04-06 | パナソニックＩｐマネジメント株式会社 | 情報端末の制御方法及びプログラム |
| WO2017056078A1 (en) | 2015-10-02 | 2017-04-06 | Koninklijke Philips N.V. | System for mapping findings to pertinent echocardiogram loops |
| JP2018534029A (ja) | 2015-10-02 | 2018-11-22 | コーニンクレッカ フィリップス エヌ ヴェＫｏｎｉｎｋｌｉｊｋｅ Ｐｈｉｌｉｐｓ Ｎ．Ｖ． | 所見を関連する心エコー図ループにマッピングするためのシステム |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2019086586A1 (en) | 2019-05-09 |
| EP3704707B1 (en) | 2024-01-10 |
| CN111448614B (zh) | 2024-05-28 |
| US20210219922A1 (en) | 2021-07-22 |
| CN111448614A (zh) | 2020-07-24 |
| EP3704707A1 (en) | 2020-09-09 |
| JP2021501633A (ja) | 2021-01-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP7325411B2 (ja) | 心エコー図を分析する方法及び装置 | |
| Kusunose et al. | A deep learning approach for assessment of regional wall motion abnormality from echocardiographic images | |
| Slomka et al. | Cardiac imaging: working towards fully-automated machine analysis & interpretation | |
| US20220208355A1 (en) | Contrast-agent-free medical diagnostic imaging | |
| KR101565311B1 (ko) | 3 차원 심초음파 검사 데이터로부터 평면들의 자동 검출 | |
| CN112292086B (zh) | 超声病变评估及相关联的设备、系统和方法 | |
| JP2020511190A (ja) | 超音波分析のためのシステムおよび方法 | |
| JP2023155314A (ja) | 医用画像処理装置 | |
| Benes et al. | Automatically designed machine vision system for the localization of CCA transverse section in ultrasound images | |
| US12105174B2 (en) | Technique for determining a cardiac metric from CMR images | |
| Kagiyama et al. | Machine learning in cardiovascular imaging | |
| Johri et al. | Assessment of image quality in real time three‐dimensional dobutamine stress echocardiography: an integrated 2D/3D approach | |
| Avola et al. | MV-MS-FETE: Multi-view multi-scale feature extractor and transformer encoder for stenosis recognition in echocardiograms | |
| CN118840329A (zh) | 一种基于图神经网络的左心室射血分数评估方法 | |
| US20220192627A1 (en) | Stress echocardiogram imaging comparison tool | |
| KR20230096358A (ko) | 인공지능을 활용한 좌심실 비후 심장 초음파 영상의 분석 방법 및 장치 | |
| EP4608278B1 (en) | Echocardiogram classification with machine learning | |
| CN105451662A (zh) | 用于医学成像与信息显示的方法和系统 | |
| EP4355209A1 (en) | Synthetic echo from ecg | |
| JP7792456B2 (ja) | 超音波診断装置、記憶媒体、および学習モデル生成方法 | |
| Wang et al. | Ventricular segmentation algorithm for echocardiography based on transfer learning and GAN | |
| US20250268558A1 (en) | Non-invasive prediction of left ventricular end diastolic pressure through multi-parameter ultrasound measurements | |
| US20250288275A1 (en) | Systems and methods for tracking of cardiotoxicity in cardiooncology through use of artificial intelligence with ultrasound measured strain measurements | |
| Chen et al. | Personalized decision support for cardiology based on deep learning: an overview | |
| Yuldashev | Mathematical Modeling and Biocybernetics in Medical Diagnostic Systems |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| A521 | Request for written amendment filed |
Free format text: JAPANESE INTERMEDIATE CODE: A523 Effective date: 20211029 |
|
| A621 | Written request for application examination |
Free format text: JAPANESE INTERMEDIATE CODE: A621 Effective date: 20211029 |
|
| A977 | Report on retrieval |
Free format text: JAPANESE INTERMEDIATE CODE: A971007 Effective date: 20220921 |
|
| A131 | Notification of reasons for refusal |
Free format text: JAPANESE INTERMEDIATE CODE: A131 Effective date: 20220928 |
|
| A601 | Written request for extension of time |
Free format text: JAPANESE INTERMEDIATE CODE: A601 Effective date: 20221222 |
|
| A521 | Request for written amendment filed |
Free format text: JAPANESE INTERMEDIATE CODE: A523 Effective date: 20230322 |
|
| 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: 20230703 |
|
| A61 | First payment of annual fees (during grant procedure) |
Free format text: JAPANESE INTERMEDIATE CODE: A61 Effective date: 20230801 |
|
| R150 | Certificate of patent or registration of utility model |
Ref document number: 7325411 Country of ref document: JP Free format text: JAPANESE INTERMEDIATE CODE: R150 |