JP6907410B2 - 磁気共鳴イメージングデータ内の動きアーティファクトの深層学習に基づく処理 - Google Patents

磁気共鳴イメージングデータ内の動きアーティファクトの深層学習に基づく処理 Download PDF

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JP6907410B2
JP6907410B2 JP2020524193A JP2020524193A JP6907410B2 JP 6907410 B2 JP6907410 B2 JP 6907410B2 JP 2020524193 A JP2020524193 A JP 2020524193A JP 2020524193 A JP2020524193 A JP 2020524193A JP 6907410 B2 JP6907410 B2 JP 6907410B2
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JP2021501015A5 (enExample
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カルステン ソマー
カルステン ソマー
トム ブロシュ
トム ブロシュ
ティム フィリップ ハーダー
ティム フィリップ ハーダー
ヨヘン ケアップ
ヨヘン ケアップ
イングマル グレスリン
イングマル グレスリン
ラファエル ウィームカー
ラファエル ウィームカー
アクセル サールバチ
アクセル サールバチ
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Koninklijke Philips NV
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    • G01R33/56Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution
    • G01R33/565Correction of image distortions, e.g. due to magnetic field inhomogeneities
    • G01R33/56509Correction of image distortions, e.g. due to magnetic field inhomogeneities due to motion, displacement or flow, e.g. gradient moment nulling
    • GPHYSICS
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    • G06T2207/100764D tomography; Time-sequential 3D tomography
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    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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JP2020524193A 2017-10-31 2018-10-22 磁気共鳴イメージングデータ内の動きアーティファクトの深層学習に基づく処理 Active JP6907410B2 (ja)

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EP17199301.7 2017-10-31
EP17199301.7A EP3477583A1 (en) 2017-10-31 2017-10-31 Deep-learning based processing of motion artifacts in magnetic resonance imaging data
PCT/EP2018/078863 WO2019086284A1 (en) 2017-10-31 2018-10-22 Deep-learning based processing of motion artifacts in magnetic resonance imaging data

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JP2021501015A5 JP2021501015A5 (enExample) 2021-04-22
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US (1) US11320508B2 (enExample)
EP (2) EP3477583A1 (enExample)
JP (1) JP6907410B2 (enExample)
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Families Citing this family (37)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11633123B2 (en) 2017-10-31 2023-04-25 Koninklijke Philips N.V. Motion artifact prediction during data acquisition
US10698063B2 (en) * 2017-11-01 2020-06-30 Siemens Healthcare Gmbh Motion artifact reduction of magnetic resonance images with an adversarial trained network
WO2019169393A1 (en) * 2018-03-02 2019-09-06 The General Hospital Corporation Improved multi-shot echo planar imaging through machine learning
US11681001B2 (en) * 2018-03-09 2023-06-20 The Board Of Trustees Of The Leland Stanford Junior University Deep learning method for nonstationary image artifact correction
WO2019218000A1 (en) * 2018-05-15 2019-11-21 Monash University Method and system of motion correction for magnetic resonance imaging
CN120370238A (zh) 2018-07-30 2025-07-25 海珀菲纳股份有限公司 用于磁共振图像重建的深度学习技术的系统、方法、存储介质以及磁共振成像系统
JP7443366B2 (ja) * 2018-08-07 2024-03-05 メタ プラットフォームズ, インク. 画像強調のための人工知能技法
US11789104B2 (en) 2018-08-15 2023-10-17 Hyperfine Operations, Inc. Deep learning techniques for suppressing artefacts in magnetic resonance images
US10818386B2 (en) * 2018-11-21 2020-10-27 Enlitic, Inc. Multi-label heat map generating system
US11324418B2 (en) 2019-03-14 2022-05-10 Hyperfine Operations, Inc. Multi-coil magnetic resonance imaging using deep learning
EP3745153A1 (en) * 2019-05-28 2020-12-02 Koninklijke Philips N.V. A method for motion artifact detection
US11726209B2 (en) 2019-06-25 2023-08-15 Faro Technologies, Inc. Artifact filtering using artificial intelligence
EP3757940B1 (de) 2019-06-26 2025-04-16 Siemens Healthineers AG Ermittlung einer patientenbewegung während einer medizinischen bildgebungsmessung
EP3839547A1 (en) * 2019-12-16 2021-06-23 Koninklijke Philips N.V. Sense magnetic resonance imaging reconstruction using neural networks
CN111223066B (zh) * 2020-01-17 2024-06-11 上海联影医疗科技股份有限公司 运动伪影校正方法、装置、计算机设备和可读存储介质
CN111325161B (zh) * 2020-02-25 2023-04-18 四川翼飞视科技有限公司 一种基于注意力机制的人脸检测神经网络的构建方法
WO2021211068A1 (en) * 2020-04-15 2021-10-21 Aselsan Elektroni̇k Sanayi̇ Ve Ti̇caret Anoni̇m Şi̇rketi̇ A method for training shallow convolutional neural networks for infrared target detection using a two-phase learning strategy
EP3916417A1 (en) 2020-05-28 2021-12-01 Koninklijke Philips N.V. Correction of magnetic resonance images using multiple magnetic resonance imaging system configurations
EP3910359A1 (en) * 2020-05-12 2021-11-17 Koninklijke Philips N.V. Machine learning based detection of motion corrupted magnetic resonance imaging data
JP7551336B2 (ja) * 2020-05-21 2024-09-17 キヤノン株式会社 情報処理装置、情報処理方法、およびプログラム
EP3933758B1 (en) 2020-07-02 2025-11-19 Siemens Healthineers AG Method and system for generating a medical image with localized artifacts using machine learning
US20220013231A1 (en) * 2020-07-13 2022-01-13 Corsmed Ab Method for ai applications in mri simulation
CN111815730B (zh) * 2020-07-15 2024-03-29 东软教育科技集团有限公司 生成含有运动伪影的ct图像的方法、装置及存储介质
US11346912B2 (en) * 2020-07-23 2022-05-31 GE Precision Healthcare LLC Systems and methods of generating robust phase images in magnetic resonance images
EP3975125A1 (en) * 2020-09-24 2022-03-30 Koninklijke Philips N.V. Anonymous fingerprinting of medical images
US11360179B2 (en) 2020-10-29 2022-06-14 The Mitre Corporation Systems and methods for estimating magnetic susceptibility through continuous motion in an MRI scanner
CN113192014B (zh) * 2021-04-16 2024-01-30 深圳市第二人民医院(深圳市转化医学研究院) 改进脑室分割模型的训练方法、装置、电子设备和介质
US11948288B2 (en) * 2021-06-07 2024-04-02 Shanghai United Imaging Intelligence Co., Ltd. Motion artifacts simulation
US12045958B2 (en) * 2021-07-16 2024-07-23 Shanghai United Imaging Intelligence Co., Ltd. Motion artifact correction using artificial neural networks
US12136484B2 (en) 2021-11-05 2024-11-05 Altis Labs, Inc. Method and apparatus utilizing image-based modeling in healthcare
EP4202468A1 (en) 2021-12-23 2023-06-28 Orbem GmbH Direct inference based on undersampled mri data of humans or animals
EP4202427A1 (en) 2021-12-23 2023-06-28 Orbem GmbH Direct inference based on undersampled mri data of industrial samples
US12475564B2 (en) 2022-02-16 2025-11-18 Proscia Inc. Digital pathology artificial intelligence quality check
CN114862680B (zh) * 2022-05-12 2025-10-21 上海电气控股集团有限公司智惠医疗装备分公司 一种图像重建方法、装置及电子设备
CN115100310A (zh) * 2022-06-27 2022-09-23 杭州微影医疗科技有限公司 一种磁共振磁敏感伪影的自动提示方法及系统
CN115797729B (zh) * 2023-01-29 2023-05-09 有方(合肥)医疗科技有限公司 模型训练方法及装置、运动伪影识别及提示的方法及装置
EP4545954A1 (en) 2023-10-26 2025-04-30 Orbem GmbH Method for enabling high-throughput imaging of industrial samples

Family Cites Families (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP4919408B2 (ja) * 2007-01-12 2012-04-18 富士フイルム株式会社 放射線画像処理方法および装置ならびにプログラム
EP2232443A4 (en) * 2008-01-10 2012-07-04 Agency Science Tech & Res DISTINCTION OF INFARTS AND ARTIFACTS IN MRI COLLECTION DATA
CN102077108B (zh) * 2008-04-28 2015-02-25 康奈尔大学 分子mri中的磁敏度精确量化
US20110077484A1 (en) * 2009-09-30 2011-03-31 Nellcor Puritan Bennett Ireland Systems And Methods For Identifying Non-Corrupted Signal Segments For Use In Determining Physiological Parameters
US10321892B2 (en) 2010-09-27 2019-06-18 Siemens Medical Solutions Usa, Inc. Computerized characterization of cardiac motion in medical diagnostic ultrasound
EP2624748B1 (en) * 2010-10-07 2024-05-01 The Medical Research, Infrastructure, And Health Services Fund Of The Tel Aviv Medical Center Device for use in electro-biological signal measurement in the presence of a magnetic field
JP2015518769A (ja) * 2012-06-05 2015-07-06 コーニンクレッカ フィリップス エヌ ヴェ 画像処理システム及び画像処理方法
US9788761B2 (en) * 2014-02-27 2017-10-17 Toshiba Medical Systems Corporation Motion correction for magnetic resonance angiography (MRA) with 3D radial acquisitions
WO2015175806A1 (en) 2014-05-16 2015-11-19 The Trustees Of The University Of Pennsylvania Applications of automatic anatomy recognition in medical tomographic imagery based on fuzzy anatomy models
DE102015212953B4 (de) 2015-07-10 2024-08-22 Siemens Healthineers Ag Künstliche neuronale Netze zur Klassifizierung von medizinischen Bilddatensätzen
US10521902B2 (en) 2015-10-14 2019-12-31 The Regents Of The University Of California Automated segmentation of organ chambers using deep learning methods from medical imaging
CA3078728A1 (en) * 2017-10-09 2019-04-18 The Board Of Trustees Of The Leland Stanford Junior University Contrast dose reduction for medical imaging using deep learning

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WO2019086284A1 (en) 2019-05-09
US11320508B2 (en) 2022-05-03
EP3704666B1 (en) 2021-06-16
EP3477583A1 (en) 2019-05-01
CN111295687A (zh) 2020-06-16
CN111295687B (zh) 2024-05-21
JP2021501015A (ja) 2021-01-14
US20210181287A1 (en) 2021-06-17
EP3704666A1 (en) 2020-09-09

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