JP7229996B2 - 流れを視覚化するための機械学習を使用したスペックルコントラスト分析 - Google Patents
流れを視覚化するための機械学習を使用したスペックルコントラスト分析 Download PDFInfo
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- G06T7/0012—Biomedical image inspection
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- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
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- 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
- G06F18/217—Validation; Performance evaluation; Active pattern learning techniques
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- 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
- G06V10/774—Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
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- 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
- G06V10/778—Active pattern-learning, e.g. online learning of image or video features
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- G—PHYSICS
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- G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
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- 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
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- G—PHYSICS
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- G—PHYSICS
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- G—PHYSICS
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- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30101—Blood vessel; Artery; Vein; Vascular
- G06T2207/30104—Vascular flow; Blood flow; Perfusion
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Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US201762551997P | 2017-08-30 | 2017-08-30 | |
| US62/551,997 | 2017-08-30 | ||
| PCT/US2018/046530 WO2019046003A1 (en) | 2017-08-30 | 2018-08-13 | GRANULARITY CONTRAST ANALYSIS USING AUTOMATIC LEARNING TO VISUALIZE A FLOW |
Publications (4)
| Publication Number | Publication Date |
|---|---|
| JP2020532783A JP2020532783A (ja) | 2020-11-12 |
| JPWO2019046003A5 JPWO2019046003A5 (https=) | 2022-04-08 |
| JP2020532783A5 JP2020532783A5 (https=) | 2022-04-08 |
| JP7229996B2 true JP7229996B2 (ja) | 2023-02-28 |
Family
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Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2020503912A Active JP7229996B2 (ja) | 2017-08-30 | 2018-08-13 | 流れを視覚化するための機械学習を使用したスペックルコントラスト分析 |
Country Status (5)
| Country | Link |
|---|---|
| US (2) | US10776667B2 (https=) |
| EP (1) | EP3676797B1 (https=) |
| JP (1) | JP7229996B2 (https=) |
| CN (2) | CN111052180A (https=) |
| WO (1) | WO2019046003A1 (https=) |
Families Citing this family (18)
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| JP7229996B2 (ja) | 2017-08-30 | 2023-02-28 | ヴェリリー ライフ サイエンシズ エルエルシー | 流れを視覚化するための機械学習を使用したスペックルコントラスト分析 |
| NL2021837B1 (en) * | 2018-10-19 | 2020-05-13 | Stichting Vu | Multimode waveguide imaging |
| US11373298B2 (en) * | 2019-03-28 | 2022-06-28 | Canon Medical Systems Corporation | Apparatus and method for training neural networks using small, heterogeneous cohorts of training data |
| JP7595421B2 (ja) * | 2019-06-10 | 2024-12-06 | 株式会社Preferred Networks | 学習用データセットの作成方法、学習用データ作成装置、訓練装置、及び、推定装置 |
| CN114364298A (zh) * | 2019-09-05 | 2022-04-15 | 奥林巴斯株式会社 | 内窥镜系统、处理系统、内窥镜系统的工作方法以及图像处理程序 |
| CN110659591B (zh) * | 2019-09-07 | 2022-12-27 | 中国海洋大学 | 基于孪生网络的sar图像变化检测方法 |
| KR102694574B1 (ko) * | 2019-10-16 | 2024-08-12 | 삼성전자주식회사 | 컴퓨팅 장치 및 그 동작 방법 |
| WO2021081253A1 (en) | 2019-10-22 | 2021-04-29 | Tempus Labs, Inc. | Systems and methods for predicting therapeutic sensitivity |
| EP4070232A4 (en) | 2019-12-05 | 2024-01-31 | Tempus Labs, Inc. | SYSTEMS AND METHODS FOR HIGH-THROUGHPUT ACTIVE SCREENING |
| CN111260586B (zh) * | 2020-01-20 | 2023-07-04 | 北京百度网讯科技有限公司 | 扭曲文档图像的矫正方法和装置 |
| US11561178B2 (en) | 2020-04-20 | 2023-01-24 | Tempus Labs, Inc. | Artificial fluorescent image systems and methods |
| US11393182B2 (en) * | 2020-05-29 | 2022-07-19 | X Development Llc | Data band selection using machine learning |
| JP7641722B2 (ja) * | 2020-10-12 | 2025-03-07 | ポーラ化成工業株式会社 | 肌の評価方法 |
| CN112288008B (zh) * | 2020-10-29 | 2022-03-01 | 四川九洲电器集团有限责任公司 | 一种基于深度学习的马赛克多光谱图像伪装目标检测方法 |
| JP2024532069A (ja) * | 2021-08-19 | 2024-09-05 | アルコン インコーポレイティド | 増強された眼科画像を生成するためのシステム及び方法 |
| KR102809814B1 (ko) * | 2022-03-24 | 2025-05-22 | (주)힉스컴퍼니 | 스펙클 패턴 기반의 피부 특징 분석 방법 및 장치 |
| CN115984405B (zh) * | 2023-01-12 | 2024-03-29 | 中国科学院宁波材料技术与工程研究所 | 基于自相关性增强的散射成像方法、系统及模型训练方法 |
| CN119887971B (zh) * | 2024-12-18 | 2025-10-17 | 杭州电子科技大学 | 一种基于散斑相关与迁移学习的实时成像方法及系统 |
Citations (1)
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| WO2016061052A1 (en) | 2014-10-14 | 2016-04-21 | East Carolina University | Methods, systems and computer program products for visualizing anatomical structures and blood flow and perfusion physiology using imaging techniques |
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| KR101025490B1 (ko) | 2003-06-12 | 2011-04-04 | 브라코 인터내셔날 비.브이. | 초음파 콘트라스트 조영에서 보충 커브 피팅을 통한 혈류 개산 |
| US7397935B2 (en) * | 2004-05-10 | 2008-07-08 | Mediguide Ltd. | Method for segmentation of IVUS image sequences |
| US9672471B2 (en) * | 2007-12-18 | 2017-06-06 | Gearbox Llc | Systems, devices, and methods for detecting occlusions in a biological subject including spectral learning |
| WO2013096546A1 (en) | 2011-12-21 | 2013-06-27 | Volcano Corporation | Method for visualizing blood and blood-likelihood in vascular images |
| US11206990B2 (en) * | 2013-01-23 | 2021-12-28 | Pedra Technology Pte Ltd | Deep tissue flowmetry using diffuse speckle contrast analysis |
| WO2014152919A1 (en) * | 2013-03-14 | 2014-09-25 | Arizona Board Of Regents, A Body Corporate Of The State Of Arizona For And On Behalf Of Arizona State University | Kernel sparse models for automated tumor segmentation |
| US8824752B1 (en) * | 2013-03-15 | 2014-09-02 | Heartflow, Inc. | Methods and systems for assessing image quality in modeling of patient anatomic or blood flow characteristics |
| US9717417B2 (en) * | 2014-10-29 | 2017-08-01 | Spectral Md, Inc. | Reflective mode multi-spectral time-resolved optical imaging methods and apparatuses for tissue classification |
| WO2016094439A1 (en) * | 2014-12-08 | 2016-06-16 | Munoz Luis Daniel | Device, system and methods for assessing tissue structures, pathology, and healing |
| US9839483B2 (en) * | 2015-04-21 | 2017-12-12 | Heartflow, Inc. | Systems and methods for risk assessment and treatment planning of arterio-venous malformation |
| CN106980899B (zh) | 2017-04-01 | 2020-11-17 | 北京昆仑医云科技有限公司 | 预测血管树血管路径上的血流特征的深度学习模型和系统 |
| JP7229996B2 (ja) | 2017-08-30 | 2023-02-28 | ヴェリリー ライフ サイエンシズ エルエルシー | 流れを視覚化するための機械学習を使用したスペックルコントラスト分析 |
-
2018
- 2018-08-13 JP JP2020503912A patent/JP7229996B2/ja active Active
- 2018-08-13 WO PCT/US2018/046530 patent/WO2019046003A1/en not_active Ceased
- 2018-08-13 CN CN201880055861.6A patent/CN111052180A/zh active Pending
- 2018-08-13 US US16/101,653 patent/US10776667B2/en active Active
- 2018-08-13 CN CN202210409469.5A patent/CN114820494B/zh active Active
- 2018-08-13 EP EP18765240.9A patent/EP3676797B1/en active Active
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2020
- 2020-07-27 US US16/939,301 patent/US11514270B2/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2016061052A1 (en) | 2014-10-14 | 2016-04-21 | East Carolina University | Methods, systems and computer program products for visualizing anatomical structures and blood flow and perfusion physiology using imaging techniques |
Non-Patent Citations (3)
| Title |
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| Kausik Basak et al.,Learning of speckle statistics for in vivoand noninvasive characterization of cutaneous wound regions using laser specklecontrast imaging,MICROVASCULAR RESEARCH,米国,ACADEMIC PRESS,2016年04月27日,VOL:107,PAGE(S):6 - 16,http://dx.doi.org/10.1016/j.mvr.2016.04.008 |
| Nicholas Vincent et al.,Detection of Hyperperfusion on Arterial Spin Labeling using Deep Learning,[online],2015年,https://ieeexplore.ieee.org/document/7359870 |
| 石川咲絵,外2名,サポートベクターマシンにおける最適解の性質,[online],2012年,https://core.ac.uk/download/pdf/235255656.pdf |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2019046003A1 (en) | 2019-03-07 |
| JP2020532783A (ja) | 2020-11-12 |
| US20200356820A1 (en) | 2020-11-12 |
| EP3676797B1 (en) | 2023-07-19 |
| US10776667B2 (en) | 2020-09-15 |
| CN114820494A (zh) | 2022-07-29 |
| US11514270B2 (en) | 2022-11-29 |
| CN114820494B (zh) | 2023-08-29 |
| EP3676797A1 (en) | 2020-07-08 |
| CN111052180A (zh) | 2020-04-21 |
| US20190065905A1 (en) | 2019-02-28 |
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