JP7542060B2 - 教師あり学習によって訓練された予測モデルによるｍｒｉ画像の予測 - Google Patents

教師あり学習によって訓練された予測モデルによるｍｒｉ画像の予測 Download PDF

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JP7542060B2
JP7542060B2 JP2022517510A JP2022517510A JP7542060B2 JP 7542060 B2 JP7542060 B2 JP 7542060B2 JP 2022517510 A JP2022517510 A JP 2022517510A JP 2022517510 A JP2022517510 A JP 2022517510A JP 7542060 B2 JP7542060 B2 JP 7542060B2
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mri images
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マルティン、ローラー
アルトゥール、ユベール、ザ、サード
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R33/00—Arrangements or instruments for measuring magnetic variables
    • G01R33/20—Arrangements or instruments for measuring magnetic variables involving magnetic resonance
    • G01R33/44—Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
    • G01R33/48—NMR imaging systems
    • G01R33/54—Signal processing systems, e.g. using pulse sequences ; Generation or control of pulse sequences; Operator console
    • G01R33/56—Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution
    • G01R33/5601—Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution involving use of a contrast agent for contrast manipulation, e.g. a paramagnetic, super-paramagnetic, ferromagnetic or hyperpolarised contrast agent
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0033—Features or image-related aspects of imaging apparatus, e.g. for MRI, optical tomography or impedance tomography apparatus; Arrangements of imaging apparatus in a room
    • A61B5/004—Features or image-related aspects of imaging apparatus, e.g. for MRI, optical tomography or impedance tomography apparatus; Arrangements of imaging apparatus in a room adapted for image acquisition of a particular organ or body part
    • 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
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/42—Detecting, measuring or recording for evaluating the gastrointestinal, the endocrine or the exocrine systems
    • A61B5/4222—Evaluating particular parts, e.g. particular organs
    • A61B5/4244—Evaluating particular parts, e.g. particular organs liver
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
    • A61K49/00—Preparations for testing in vivo
    • A61K49/06—Nuclear magnetic resonance [NMR] contrast preparations; Magnetic resonance imaging [MRI] contrast preparations
    • A61K49/08—Nuclear magnetic resonance [NMR] contrast preparations; Magnetic resonance imaging [MRI] contrast preparations characterised by the carrier
    • A61K49/10—Organic compounds
    • A61K49/101—Organic compounds the carrier being a complex-forming compound able to form MRI-active complexes with paramagnetic metals
    • A61K49/103—Organic compounds the carrier being a complex-forming compound able to form MRI-active complexes with paramagnetic metals the complex-forming compound being acyclic, e.g. DTPA
    • 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
    • G06N3/045—Combinations of networks
    • 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]
    • 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
    • G06N3/08—Learning methods
    • G06N3/084—Backpropagation, e.g. using gradient descent
    • 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
    • G06N3/08—Learning methods
    • G06N3/09—Supervised learning
    • 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
    • G06T7/0014—Biomedical image inspection using an image reference approach
    • G06T7/0016—Biomedical image inspection using an image reference approach involving temporal comparison
    • 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
    • G06T2207/10016—Video; Image sequence
    • 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
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30056—Liver; Hepatic
    • 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
    • G06T2207/30101—Blood vessel; Artery; Vein; Vascular

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  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Theoretical Computer Science (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
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  • Biomedical Technology (AREA)
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  • Radiology & Medical Imaging (AREA)
  • General Physics & Mathematics (AREA)
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  • Veterinary Medicine (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Artificial Intelligence (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Surgery (AREA)
  • Pathology (AREA)
  • High Energy & Nuclear Physics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Quality & Reliability (AREA)
  • Gastroenterology & Hepatology (AREA)
  • Epidemiology (AREA)
  • Endocrinology (AREA)
  • Physiology (AREA)
  • Medicinal Chemistry (AREA)
  • Chemical & Material Sciences (AREA)
  • Signal Processing (AREA)
  • Condensed Matter Physics & Semiconductors (AREA)
  • Magnetic Resonance Imaging Apparatus (AREA)
  • Medicines Containing Antibodies Or Antigens For Use As Internal Diagnostic Agents (AREA)
JP2022517510A 2019-09-18 2020-09-14 教師あり学習によって訓練された予測モデルによるｍｒｉ画像の予測 Active JP7542060B2 (ja)

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EP19197989 2019-09-18
EP19197989.7 2019-09-18
PCT/EP2020/075593 WO2021052896A1 (de) 2019-09-18 2020-09-14 Vorhersage von mrt-aufnahmen durch ein mittels überwachten lernens trainiertes vorhersagemodell

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JP2022549604A5 JP2022549604A5 (enExample) 2023-07-04
JP7542060B2 true JP7542060B2 (ja) 2024-08-29

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US (2) US11727571B2 (enExample)
EP (2) EP4231037A1 (enExample)
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CN (1) CN113330483B (enExample)
AU (1) AU2020347797B2 (enExample)
ES (1) ES2955349T3 (enExample)
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Families Citing this family (17)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP4235202B1 (de) 2022-02-24 2025-12-10 Bayer Aktiengesellschaft Vorhersage einer repräsentation eines untersuchungsbereichs eines untersuchungsobjekts in einem zustand einer folge von zuständen
US20260087709A1 (en) 2022-08-30 2026-03-26 Bayer Aktiengesellschaft Generation of synthetic radiological images
WO2024046832A1 (de) 2022-08-30 2024-03-07 Bayer Aktiengesellschaft Erzeugen von synthetischen radiologischen aufnahmen
EP4336513B1 (de) 2022-08-30 2024-12-18 Bayer Aktiengesellschaft Erzeugen von synthetischen radiologischen aufnahmen
CN119816744B (zh) * 2022-09-05 2025-09-26 拜耳公司 生成人工对比度增强的放射图像
EP4336204A1 (de) 2022-09-07 2024-03-13 Bayer AG Beschleunigen von mrt-untersuchungen der leber
EP4471710B1 (de) 2023-05-30 2025-12-17 Bayer Aktiengesellschaft Erkennen von artefakten in synthetischen medizinischen aufnahmen
WO2024251601A1 (de) * 2023-06-05 2024-12-12 Bayer Aktiengesellschaft Erzeugen von künstlichen kontrastverstärkten radiologischen aufnahmen
EP4475070B1 (de) 2023-06-05 2026-04-22 Bayer Aktiengesellschaft Erkennen von artefakten in synthetischen medizinischen aufnahmen
EP4492324A1 (de) 2023-07-12 2025-01-15 Bayer AG Erkennen von artefakten in synthetischen medizinischen aufnahmen
US20250045926A1 (en) 2023-07-25 2025-02-06 Bayer Aktiengesellschaft Detection of artifacts in synthetic images
EP4560648A1 (en) 2023-11-22 2025-05-28 Bayer AG Generating synthetic training data
CN122319460A (zh) 2023-12-06 2026-06-30 拜耳公司 生成合成医学表征
EP4571650A1 (en) 2023-12-12 2025-06-18 Bayer AG Generating synthetic images
EP4575997A1 (en) 2023-12-18 2025-06-25 Bayer Aktiengesellschaft Generating synthetic images
CN122439098A (zh) 2023-12-25 2026-07-21 伯拉考成像股份公司 基于逆问题模拟医学应用中更长延迟后获取的图像
EP4672132A1 (en) 2024-06-26 2025-12-31 Bayer Aktiengesellschaft GENERATION OF SYNTHETIC RADIOLOGICAL IMAGES

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002165775A (ja) 2000-12-01 2002-06-11 Hitachi Medical Corp 磁気共鳴イメージング装置
JP2003519200A (ja) 1999-12-29 2003-06-17 ブラッコ イメージング エッセ ピ ア 腸管腔の視覚化のための診断剤の製造における造影剤の使用
US20100198054A1 (en) 2007-05-18 2010-08-05 Ewing James R Mri estimation of contrast agent concentration using a neural network approach
JP2017064370A (ja) 2015-09-29 2017-04-06 キヤノン株式会社 画像処理装置、画像処理装置の制御方法およびプログラム
JP6491391B1 (ja) 2018-11-22 2019-03-27 国立大学法人信州大学 血流動態解析システム、血流動態解析方法、およびプログラム
US20190108634A1 (en) 2017-10-09 2019-04-11 The Board Of Trustees Of The Leland Stanford Junior University Contrast Dose Reduction for Medical Imaging Using Deep Learning
US20190122348A1 (en) 2017-10-20 2019-04-25 Imaging Biometrics, Llc Simulated Post-Contrast T1-Weighted Magnetic Resonance Imaging

Family Cites Families (102)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US732697A (en) 1903-02-19 1903-07-07 John Davis Bates Lumber-surface meter.
US3060178A (en) 1960-01-04 1962-10-23 Merck & Co Inc Derivatives of benzothiadiazine-1, 1-dioxide
US6039931A (en) 1989-06-30 2000-03-21 Schering Aktiengesellschaft Derivatized DTPA complexes, pharmaceutical agents containing these compounds, their use, and processes for their production
US5840026A (en) 1994-09-21 1998-11-24 Medrad, Inc. Patient specific dosing contrast delivery systems and methods
US6397098B1 (en) 1994-09-21 2002-05-28 Medrad, Inc. Data communication and control for medical imaging systems
US5732697A (en) 1995-11-22 1998-03-31 Arch Development Corporation Shift-invariant artificial neural network for computerized detection of clustered microcalcifications in mammography
US6339718B1 (en) 1999-07-30 2002-01-15 Medrad, Inc. Programmable injector control
US6754376B1 (en) 2000-11-22 2004-06-22 General Electric Company Method for automatic segmentation of medical images
US6819790B2 (en) 2002-04-12 2004-11-16 The University Of Chicago Massive training artificial neural network (MTANN) for detecting abnormalities in medical images
US7458936B2 (en) 2003-03-12 2008-12-02 Siemens Medical Solutions Usa, Inc. System and method for performing probabilistic classification and decision support using multidimensional medical image databases
US7545965B2 (en) 2003-11-10 2009-06-09 The University Of Chicago Image modification and detection using massive training artificial neural networks (MTANN)
WO2006093523A2 (en) 2004-07-15 2006-09-08 Kenji Suzuki Computerized scheme for distinction between benign and malignant nodules in thoracic low-dose ct
US7567832B2 (en) * 2004-08-13 2009-07-28 The Mcw Research Foundation MRI method for measuring tumor hemodynamic parameters in the presence of contrast agent extravasation
WO2006055813A2 (en) 2004-11-16 2006-05-26 Medrad, Inc. Modeling of pharmaceutical propagation
US7738683B2 (en) 2005-07-22 2010-06-15 Carestream Health, Inc. Abnormality detection in medical images
US7564990B2 (en) 2005-08-18 2009-07-21 Nu Skin International, Inc. Imaging system and method for physical feature analysis
US7343032B2 (en) 2005-09-01 2008-03-11 Fujifilm Corporation Method and apparatus for automatic and dynamic vessel detection
EP1780677A1 (en) 2005-10-25 2007-05-02 BRACCO IMAGING S.p.A. Image processing system, particularly for use with diagnostics images
US7840044B2 (en) 2005-11-01 2010-11-23 Edda Technology Inc. Method and system for liver lobe segmentation and pre-operative surgical planning
US20220031270A1 (en) 2007-03-08 2022-02-03 Sync-Rx, Ltd Identification an dpresentation of device-tovessel relative motion
WO2008155738A2 (en) * 2007-06-21 2008-12-24 Koninklijke Philips Electronics N.V. Adjusting acquisition protocols for dynamic medical imaging using dynamic models
DE102007028660B3 (de) 2007-06-21 2009-01-29 Siemens Ag Verfahren zur Korrektur von Bewegungsartefakten bei der Aufnahme von MR-Bildern
WO2009098627A1 (en) 2008-02-07 2009-08-13 Koninklijke Philips Electronics N.V. Apparatus for measuring and predicting patients' respiratory stability
WO2009135923A1 (en) 2008-05-08 2009-11-12 Oslo Universitetssykehus Hf Vessel segmentation in dce mr imaging
US7949167B2 (en) 2008-06-12 2011-05-24 Siemens Medical Solutions Usa, Inc. Automatic learning of image features to predict disease
US8452065B2 (en) * 2009-03-11 2013-05-28 Fred S. Azar System for detecting malignant lymph nodes using an MR imaging device
EP2528493B1 (en) 2010-01-28 2017-04-19 Brainlab AG Method and apparatus for estimating temperature in a body
US8478698B1 (en) 2010-03-17 2013-07-02 James Mah Methods and systems for employing artificial intelligence in automated orthodontic diagnosis and treatment planning
RU2725751C9 (ru) 2010-12-08 2020-12-21 БАЙЕР ХелсКер ЛЛСи Создание подходящей модели для оценки дозы облучения пациента в результате сканирований для медицинской визуализации
FR2979453B1 (fr) 2011-08-26 2016-01-08 Olea Medical Systeme et procede pour estimer une quantite d'interet d'un systeme dynamique artere/tissu/veine
WO2013036842A2 (en) 2011-09-08 2013-03-14 Radlogics, Inc. Methods and systems for analyzing and reporting medical images
JP5878009B2 (ja) 2011-12-12 2016-03-08 株式会社根本杏林堂 医療用画像処理ネットワークシステム
WO2016007734A1 (en) 2014-07-09 2016-01-14 The Trustees Of Dartmouth College Methods for quantitative and enhanced-contrast molecular medical imaging using cross-modality correction for differing tracer kinetics
EP2626718A1 (en) 2012-02-09 2013-08-14 Koninklijke Philips Electronics N.V. MRI with motion correction using navigators acquired using a Dixon technique
RU2629799C2 (ru) 2012-02-17 2017-09-04 Конинклейке Филипс Н.В. Оценка и наблюдение острого повреждения легких (ali)/синдрома острой дыхательной недостаточности (ards)
WO2013169353A1 (en) 2012-05-11 2013-11-14 University Of Iowa Research Foundation Multimodal imaging methods using mesoporous silica nanoparticles
DE102012215718B4 (de) 2012-09-05 2022-05-12 Siemens Healthcare Gmbh Verfahren und Magnetresonanzanlage zur MR-Bildgebung eines vorbestimmten Volumenabschnitts eines lebenden Untersuchungsobjekts mittels Stimulieren des Untersuchungsobjekts
US9449381B2 (en) 2012-09-10 2016-09-20 Arizona Board Of Regents, A Body Corporate Of The State Of Arizona, Acting For And On Behalf Of Arizona State University Methods, systems, and media for generating and analyzing medical images having elongated structures
WO2014068520A1 (en) 2012-10-31 2014-05-08 Koninklijke Philips N.V. Perfusion imaging
EP2750102B2 (en) 2012-12-27 2025-12-10 General Electric Company Method, system and computer readable medium for liver analysis
US9901650B2 (en) 2013-02-21 2018-02-27 University Of Rochester Methods for evaluating brain-wide paravascular pathway for waste clearance function and methods for treating neurodegenerative disorders based thereon
US10089744B2 (en) 2013-04-03 2018-10-02 Koninklijke Philips N.V. Vessel segmentation
EP2988668B1 (en) 2013-04-24 2019-07-24 Tel HaShomer Medical Research Infrastructure and Services Ltd. Magnetic resonance maps for analyzing tissue
CN103914622B (zh) * 2014-04-04 2017-07-07 清华大学 一种化学品泄漏快速预测预警应急响应决策方法
WO2016019347A1 (en) 2014-07-31 2016-02-04 California Institute Of Technology Multi modality brain mapping system (mbms) using artificial intelligence and pattern recognition
US20160038092A1 (en) 2014-08-11 2016-02-11 Douglas A. Golay Applying non-real time and non-user attended algorithms to stored non-imaging data and existing imaging data for obtaining a dental diagnosis
US10061003B2 (en) 2014-09-01 2018-08-28 bioProtonics, L.L.C. Selective sampling for assessing structural spatial frequencies with specific contrast mechanisms
US10176573B2 (en) 2014-10-13 2019-01-08 Agency For Science, Technology And Research Automatic region-of-interest segmentation and registration of dynamic contrast-enhanced images of colorectal tumors
WO2016084373A1 (ja) * 2014-11-27 2016-06-02 国立大学法人広島大学 シミュレータ、該シミュレータを備える注入装置又は撮像システム、及びシミュレーションプログラム
JP2018511791A (ja) 2015-02-27 2018-04-26 バイエル・ヘルスケア・エルエルシーＢａｙｅｒ ＨｅａｌｔｈＣａｒｅ ＬＬＣ マルチイメージングモダリティ用定量的ファントム
US9959615B2 (en) 2015-07-01 2018-05-01 Arizona Board Of Regents On Behalf Of Arizona State University System and method for automatic pulmonary embolism detection
US20170016972A1 (en) 2015-07-13 2017-01-19 Siemens Medical Solutions Usa, Inc. Fast Prospective Motion Correction For MR Imaging
US10634753B2 (en) 2015-07-15 2020-04-28 Koninklijke Philips N.V. MR imaging with motion detection
US10157467B2 (en) 2015-08-07 2018-12-18 Arizona Board Of Regents On Behalf Of Arizona State University System and method for detecting central pulmonary embolism in CT pulmonary angiography images
US10176408B2 (en) 2015-08-14 2019-01-08 Elucid Bioimaging Inc. Systems and methods for analyzing pathologies utilizing quantitative imaging
WO2017035097A1 (en) 2015-08-21 2017-03-02 Duke University Systems and methods for determining image quality and models based on contrast injection protocols
DK3341048T3 (da) 2015-08-28 2023-08-21 Bayer Healthcare Llc System og fremgangsmåde til verificering af sprøjtefluidfyldning og billedgenkendelse af træk ved kraftinjektorsystem
US10645359B2 (en) 2015-12-16 2020-05-05 B<>Com Method for processing a digital image, device, terminal equipment and associated computer program
US9786058B2 (en) 2016-02-08 2017-10-10 Sony Corporation Method and system for segmentation of vascular structure in a volumetric image dataset
US20170245817A1 (en) 2016-02-10 2017-08-31 The Charles Stark Draper Laboratory, Inc. Systems and methods for imaging
DE102016204198B4 (de) 2016-03-15 2018-06-07 Siemens Healthcare Gmbh Verfahren zur Erzeugung von MR-Bildern mit prospektiver Bewegungskorrektur und teilvolumenspezifischer Gewichtung der Bildinformation
US10282588B2 (en) 2016-06-09 2019-05-07 Siemens Healthcare Gmbh Image-based tumor phenotyping with machine learning from synthetic data
WO2018048507A1 (en) * 2016-09-06 2018-03-15 Han Xiao Neural network for generating synthetic medical images
US11544529B2 (en) 2016-09-07 2023-01-03 Koninklijke Philips N.V. Semi-supervised classification with stacked autoencoder
AU2017345167B2 (en) 2016-10-17 2022-12-15 Bayer Healthcare Llc Fluid injector with syringe engagement mechanism
CA3043038A1 (en) 2016-11-22 2018-05-31 Hyperfine Research, Inc. Systems and methods for automated detection in magnetic resonance images
US10933186B2 (en) 2016-11-22 2021-03-02 Bayer Healthcare Llc System and method for delivering a fluid with a consistent total volumetric flowrate
US10096109B1 (en) 2017-03-31 2018-10-09 The Board Of Trustees Of The Leland Stanford Junior University Quality of medical images using multi-contrast and deep learning
JP7179757B2 (ja) 2017-04-25 2022-11-29 ザ ボード オブ トラスティーズ オブ ザ レランド スタンフォード ジュニア ユニバーシティー ディープ畳み込みニューラルネットワークを使用した医用画像化のための線量低減
US20180315183A1 (en) 2017-04-28 2018-11-01 General Electric Company System and method for monitoring an amount of a contrast agent within an object
WO2018202541A1 (de) 2017-05-02 2018-11-08 Bayer Aktiengesellschaft Verbesserungen bei der radiologischen erkennung chronisch thromboembolischer pulmonaler hypertonie
JP6920904B2 (ja) 2017-07-04 2021-08-18 国立大学法人広島大学 シミュレータ、該シミュレータを備える注入装置又は撮像システム、及びシミュレーションプログラム
AU2018323442B2 (en) 2017-08-31 2024-06-27 Bayer Healthcare Llc Fluid path impedance assessment for improving fluid delivery performance
US11631485B2 (en) 2017-09-26 2023-04-18 Koninklijke Philips N.V. System and method for joint clinical decision for pharmaceuticals
US10335106B2 (en) 2017-09-29 2019-07-02 Infinitt Healthcare Co., Ltd. Computing system and method for identifying and visualizing cerebral thrombosis based on medical images
CN118866316A (zh) 2017-10-31 2024-10-29 通用电气健康护理有限公司 用于诊断认知疾病病理和/或结果的医疗系统
WO2019102846A1 (ja) 2017-11-24 2019-05-31 キヤノンメディカルシステムズ株式会社 医用データ処理装置、磁気共鳴イメージング装置及び学習済みモデル生成方法
CN108324244A (zh) * 2018-01-03 2018-07-27 华东师范大学 用于ai+mri影像辅助诊断的自动增广训练样本的构建方法及系统
KR102001398B1 (ko) 2018-01-25 2019-07-18 재단법인 아산사회복지재단 기계학습을 통한 뇌질환 상태변화 예측방법, 장치 및 프로그램
WO2019161043A1 (en) * 2018-02-15 2019-08-22 GE Precision Healthcare LLC System and method for synthesizing magnetic resonance images
WO2019183555A1 (en) 2018-03-22 2019-09-26 The University Of North Carolina At Chapel Hill Methods, systems and computer readable media for processing digital subtraction angiography (dsa) and computed tomography (ct) images for reducing radiation exposure in dsa and ct subjects
US11982726B2 (en) 2018-04-13 2024-05-14 University Of Southern California Method for joint arterial input function and tracer kinetic parameter estimation in accelerated DCE-MRI using a model consistency constraint
US11100632B2 (en) * 2018-04-13 2021-08-24 Elekta, Inc. Image synthesis using adversarial networks such as for radiation therapy
US20190347772A1 (en) 2018-04-19 2019-11-14 Subtle Medical, Inc. Systems and methods for improving magnetic resonance imaging using deep learning
CN108703764B (zh) 2018-05-29 2021-11-05 北京东软医疗设备有限公司 血管造影方法、装置、系统、设备及存储介质
WO2019241659A1 (en) 2018-06-15 2019-12-19 Subtle Medical, Inc. Systems and methods for magnetic resonance imaging standardization using deep learning
EP3649955A1 (en) * 2018-11-07 2020-05-13 Koninklijke Philips N.V. Deep learning based spectral bolus tracking
EP3657433B1 (en) 2018-11-22 2022-10-19 Siemens Healthcare GmbH Medical image data
DE102018222606A1 (de) 2018-12-20 2020-06-25 Siemens Healthcare Gmbh Verfahren und Vorrichtung zur Detektion eines anatomischen Merkmals eines Blutgefäßabschnittes
US10867375B2 (en) * 2019-01-30 2020-12-15 Siemens Healthcare Gmbh Forecasting images for image processing
US11398026B2 (en) * 2019-03-28 2022-07-26 The Board Of Trustees Of The Leland Stanford Junior University Systems and methods for synthetic medical image generation
DE102019207639A1 (de) 2019-05-24 2020-11-26 Siemens Healthcare Gmbh Verbesserte Berechnung der Kontrastmittelkonzentration
EP3756547A1 (en) 2019-06-28 2020-12-30 Koninklijke Philips N.V. Automated coronary angiography analysis
US20210012486A1 (en) * 2019-07-09 2021-01-14 Shenzhen Malong Technologies Co., Ltd. Image synthesis with generative adversarial network
CN110391016B (zh) 2019-07-10 2021-11-09 浙江大学 一种动态对比增强磁共振图像的分析方法
US12310741B2 (en) 2019-09-18 2025-05-27 Bayer Aktiengesellschaft Generation of MRI images of the liver
EP3804615A1 (de) 2019-10-08 2021-04-14 Bayer AG Erzeugung von mrt-aufnahmen der leber
EP4041075B1 (de) 2019-10-08 2025-08-13 Bayer Aktiengesellschaft Erzeugung von mrt-aufnahmen der leber ohne kontrastverstärkung
WO2021069343A1 (de) 2019-10-11 2021-04-15 Bayer Aktiengesellschaft Beschleunigung von mrt-untersuchungen
EP3875979A1 (de) 2020-03-06 2021-09-08 Bayer Aktiengesellschaft Optimiertes verfahren für dynamische kontrastverstärkende magnetresonanztomographie
WO2021197996A1 (de) 2020-04-03 2021-10-07 Bayer Aktiengesellschaft Erzeugen von radiologischen aufnahmen
US11308613B2 (en) 2020-06-09 2022-04-19 Siemens Healthcare Gmbh Synthesis of contrast enhanced medical images

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003519200A (ja) 1999-12-29 2003-06-17 ブラッコ イメージング エッセ ピ ア 腸管腔の視覚化のための診断剤の製造における造影剤の使用
JP2002165775A (ja) 2000-12-01 2002-06-11 Hitachi Medical Corp 磁気共鳴イメージング装置
US20100198054A1 (en) 2007-05-18 2010-08-05 Ewing James R Mri estimation of contrast agent concentration using a neural network approach
JP2017064370A (ja) 2015-09-29 2017-04-06 キヤノン株式会社 画像処理装置、画像処理装置の制御方法およびプログラム
US20190108634A1 (en) 2017-10-09 2019-04-11 The Board Of Trustees Of The Leland Stanford Junior University Contrast Dose Reduction for Medical Imaging Using Deep Learning
US20190122348A1 (en) 2017-10-20 2019-04-25 Imaging Biometrics, Llc Simulated Post-Contrast T1-Weighted Magnetic Resonance Imaging
JP6491391B1 (ja) 2018-11-22 2019-03-27 国立大学法人信州大学 血流動態解析システム、血流動態解析方法、およびプログラム

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