JP7359851B2 - 陽電子放出断層撮影(pet)のための人工知能(ai)ベースの標準取込み値(suv)補正及び変動評価 - Google Patents
陽電子放出断層撮影(pet)のための人工知能(ai)ベースの標準取込み値(suv)補正及び変動評価 Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T12/00—Tomographic reconstruction from projections
- G06T12/30—Image post-processing, e.g. metal artefact correction
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/0464—Convolutional networks [CNN, ConvNet]
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- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
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- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/09—Supervised learning
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- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computing arrangements based on specific mathematical models
- G06N7/02—Computing arrangements based on specific mathematical models using fuzzy logic
- G06N7/04—Physical realisation
- G06N7/046—Implementation by means of a neural network
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T12/00—Tomographic reconstruction from projections
- G06T12/10—Image preprocessing, e.g. calibration, positioning of sources or scatter correction
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- 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
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- 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
- G06T2207/10104—Positron emission tomography [PET]
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- 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]
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- 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
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2211/00—Image generation
- G06T2211/40—Computed tomography
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- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
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Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US201862760124P | 2018-11-13 | 2018-11-13 | |
| US62/760,124 | 2018-11-13 | ||
| PCT/EP2019/080628 WO2020099250A1 (en) | 2018-11-13 | 2019-11-08 | Artificial intelligence (ai)-based standardized uptake value (suv) correction and variation assessment for positron emission tomography (pet) |
Publications (3)
| Publication Number | Publication Date |
|---|---|
| JP2022506395A JP2022506395A (ja) | 2022-01-17 |
| JP2022506395A5 JP2022506395A5 (enExample) | 2022-11-11 |
| JP7359851B2 true JP7359851B2 (ja) | 2023-10-11 |
Family
ID=68501620
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2021523746A Active JP7359851B2 (ja) | 2018-11-13 | 2019-11-08 | 陽電子放出断層撮影(pet)のための人工知能(ai)ベースの標準取込み値(suv)補正及び変動評価 |
Country Status (5)
| Country | Link |
|---|---|
| US (1) | US12346998B2 (enExample) |
| EP (1) | EP3881289A1 (enExample) |
| JP (1) | JP7359851B2 (enExample) |
| CN (1) | CN113196340B (enExample) |
| WO (1) | WO2020099250A1 (enExample) |
Families Citing this family (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US12346998B2 (en) * | 2018-11-13 | 2025-07-01 | Koninklijke Philips N.V. | Artificial intelligence (AI)-based standardized uptake value (SUV) correction and variation assessment for positron emission tomography (PET) |
| US11429840B2 (en) * | 2019-09-25 | 2022-08-30 | Siemens Medical Solutions Usa, Inc. | Learning parameter invariant image reconstruction embedding for AI systems |
| WO2021159236A1 (zh) * | 2020-02-10 | 2021-08-19 | 深圳先进技术研究院 | 基于非衰减校正pet图像生成合成pet-ct图像的方法和系统 |
| CN113505527B (zh) * | 2021-06-24 | 2022-10-04 | 中国科学院计算机网络信息中心 | 一种基于数据驱动的材料性质预测方法及系统 |
| CN114358285B (zh) * | 2022-01-11 | 2025-04-29 | 浙江大学 | 一种基于流模型的pet系统衰减校正方法 |
| WO2023149174A1 (ja) * | 2022-02-02 | 2023-08-10 | ソニーグループ株式会社 | 情報処理装置、情報処理方法及びプログラム |
| KR102784862B1 (ko) * | 2022-05-18 | 2025-03-21 | 서울대학교산학협력단 | 복셀 기반 방사선 선량 평가 방법 및 장치 |
| CN116228909A (zh) * | 2023-03-10 | 2023-06-06 | 南京理工大学 | 基于深度卷积神经网络的pet系统晶间散射校正方法 |
| US20250225698A1 (en) * | 2024-01-10 | 2025-07-10 | Siemens Medical Solutions Usa, Inc. | Methods and apparatus for generating images for an uptake time using machine learning based processes |
| CN118151585B (zh) * | 2024-03-12 | 2024-10-08 | 河北安迪科正电子技术有限公司 | 一种基于人工智能的正电子设备自动化控制系统及方法 |
| US20250329070A1 (en) * | 2024-04-22 | 2025-10-23 | GE Precision Healthcare LLC | Data-driven system and method to access and correct system responses |
| CN120411688B (zh) * | 2025-07-01 | 2025-11-04 | 中国科学院自动化研究所 | 基于小样本的bad识别模型构建方法及bad识别方法 |
| CN120726053B (zh) * | 2025-09-01 | 2025-11-21 | 川北医学院附属医院 | 用于神经系统疾病的核医学功能成像分析方法及系统 |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140126794A1 (en) | 2012-11-02 | 2014-05-08 | General Electric Company | Systems and methods for partial volume correction in pet penalized-likelihood image reconstruction |
| WO2018187020A1 (en) | 2017-04-05 | 2018-10-11 | General Electric Company | Tomographic reconstruction based on deep learning |
| WO2018202648A1 (en) | 2017-05-01 | 2018-11-08 | Koninklijke Philips N.V. | Generation of accurate hybrid datasets for quantitative molecular imaging |
Family Cites Families (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2007144703A (ru) | 2005-05-03 | 2009-06-10 | Конинклейке Филипс Электроникс Н.В. (Nl) | Виртуальная количественная оценка очага поражения |
| US8026488B2 (en) * | 2008-01-24 | 2011-09-27 | Case Western Reserve University | Methods for positive emission tomography (PET) target image segmentation |
| RU2526717C2 (ru) | 2009-01-22 | 2014-08-27 | Конинклейке Филипс Электроникс, Н.В. | Попиксельное и поэлементное гибридное объединение для изображений позитрон-эмиссионной томографии (рет)/компьютерной томографии (ст) |
| EP2457216B1 (en) | 2009-07-20 | 2017-11-08 | Koninklijke Philips N.V. | Anatomy modeling for tumor region of interest definition |
| US8620053B2 (en) * | 2009-11-04 | 2013-12-31 | Siemens Medical Solutions Usa, Inc. | Completion of truncated attenuation maps using maximum likelihood estimation of attenuation and activity (MLAA) |
| RU2013129865A (ru) * | 2010-12-01 | 2015-01-10 | Конинклейке Филипс Электроникс Н.В. | Особенности диагностического изображения рядом с источниками артефактов |
| US9436989B2 (en) * | 2011-06-03 | 2016-09-06 | Bayer Healthcare Llc | System and method for rapid quantitative dynamic molecular imaging scans |
| EP3996039A1 (en) * | 2014-10-17 | 2022-05-11 | Stichting Maastricht Radiation Oncology "Maastro-Clinic" | Image analysis method supporting illness development prediction for a neoplasm in a human or animal body |
| CN108292443A (zh) * | 2015-11-20 | 2018-07-17 | 皇家飞利浦有限公司 | 使用病变代理的pet图像重建和处理 |
| US10311560B2 (en) | 2016-09-07 | 2019-06-04 | Huazhong University Of Science And Technology | Method and system for estimating blur kernel size |
| CN107123095B (zh) * | 2017-04-01 | 2020-03-31 | 上海联影医疗科技有限公司 | 一种pet图像重建方法、成像系统 |
| US20200175732A1 (en) * | 2017-06-02 | 2020-06-04 | Koninklijke Philips N.V. | Systems and methods to provide confidence values as a measure of quantitative assurance for iteratively reconstructed images in emission tomography |
| CN107403201A (zh) * | 2017-08-11 | 2017-11-28 | 强深智能医疗科技(昆山)有限公司 | 肿瘤放射治疗靶区和危及器官智能化、自动化勾画方法 |
| US12346998B2 (en) * | 2018-11-13 | 2025-07-01 | Koninklijke Philips N.V. | Artificial intelligence (AI)-based standardized uptake value (SUV) correction and variation assessment for positron emission tomography (PET) |
| EP4026054A4 (en) * | 2019-10-09 | 2022-11-30 | Siemens Medical Solutions USA, Inc. | IMAGE RECONSTRUCTION BY MODELING IMAGE GENERATION AS ONE OR MORE NEURAL NETWORKS |
| EP3901903B1 (en) * | 2020-04-23 | 2023-06-14 | Siemens Healthcare GmbH | Classifying a lesion based on longitudinal studies |
| EP4208848A1 (en) * | 2020-09-02 | 2023-07-12 | Genentech, Inc. | Connected machine-learning models with joint training for lesion detection |
| US20220383045A1 (en) * | 2021-05-25 | 2022-12-01 | International Business Machines Corporation | Generating pseudo lesion masks from bounding box annotations |
-
2019
- 2019-11-08 US US17/292,044 patent/US12346998B2/en active Active
- 2019-11-08 JP JP2021523746A patent/JP7359851B2/ja active Active
- 2019-11-08 WO PCT/EP2019/080628 patent/WO2020099250A1/en not_active Ceased
- 2019-11-08 EP EP19801009.2A patent/EP3881289A1/en not_active Withdrawn
- 2019-11-08 CN CN201980081881.5A patent/CN113196340B/zh active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140126794A1 (en) | 2012-11-02 | 2014-05-08 | General Electric Company | Systems and methods for partial volume correction in pet penalized-likelihood image reconstruction |
| WO2018187020A1 (en) | 2017-04-05 | 2018-10-11 | General Electric Company | Tomographic reconstruction based on deep learning |
| WO2018202648A1 (en) | 2017-05-01 | 2018-11-08 | Koninklijke Philips N.V. | Generation of accurate hybrid datasets for quantitative molecular imaging |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2020099250A8 (en) | 2020-07-30 |
| CN113196340A (zh) | 2021-07-30 |
| CN113196340B (zh) | 2025-02-18 |
| WO2020099250A1 (en) | 2020-05-22 |
| JP2022506395A (ja) | 2022-01-17 |
| US20210398329A1 (en) | 2021-12-23 |
| EP3881289A1 (en) | 2021-09-22 |
| US12346998B2 (en) | 2025-07-01 |
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