JP7757314B2 - 複数の磁気共鳴イメージングシステム構成を使用した磁気共鳴画像の補正 - Google Patents
複数の磁気共鳴イメージングシステム構成を使用した磁気共鳴画像の補正Info
- Publication number
- JP7757314B2 JP7757314B2 JP2022568522A JP2022568522A JP7757314B2 JP 7757314 B2 JP7757314 B2 JP 7757314B2 JP 2022568522 A JP2022568522 A JP 2022568522A JP 2022568522 A JP2022568522 A JP 2022568522A JP 7757314 B2 JP7757314 B2 JP 7757314B2
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- magnetic resonance
- image data
- space data
- resonance image
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Classifications
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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
-
- 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
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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
- G01R33/4818—MR characterised by data acquisition along a specific k-space trajectory or by the temporal order of k-space coverage, e.g. centric or segmented coverage of k-space
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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
- G01R33/543—Control of the operation of the MR system, e.g. setting of acquisition parameters prior to or during MR data acquisition, dynamic shimming, use of one or more scout images for scan plane prescription
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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
- G01R33/5608—Data processing and visualization specially adapted for MR, e.g. for feature analysis and pattern recognition on the basis of measured MR data, segmentation of measured MR data, edge contour detection on the basis of measured MR data, for enhancing measured MR data in terms of signal-to-noise ratio by means of noise filtering or apodization, for enhancing measured MR data in terms of resolution by means for deblurring, windowing, zero filling, or generation of gray-scaled images, colour-coded images or images displaying vectors instead of pixels
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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
- G01R33/561—Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution by reduction of the scanning time, i.e. fast acquiring systems, e.g. using echo-planar pulse sequences
-
- 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
- G01R33/565—Correction of image distortions, e.g. due to magnetic field inhomogeneities
-
- 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
- G01R33/565—Correction of image distortions, e.g. due to magnetic field inhomogeneities
- G01R33/56509—Correction of image distortions, e.g. due to magnetic field inhomogeneities due to motion, displacement or flow, e.g. gradient moment nulling
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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
- G06N3/045—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]
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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
- G06N3/0475—Generative networks
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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
- G06N3/08—Learning methods
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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
- G06N3/08—Learning methods
- G06N3/084—Backpropagation, e.g. using gradient descent
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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
- G06N3/08—Learning methods
- G06N3/09—Supervised learning
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T12/00—Tomographic reconstruction from projections
- G06T12/20—Inverse problem, i.e. transformations from projection space into object space
-
- 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
- A61B5/0042—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 for the brain
-
- 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
- G01R33/561—Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution by reduction of the scanning time, i.e. fast acquiring systems, e.g. using echo-planar pulse sequences
- G01R33/5611—Parallel magnetic resonance imaging, e.g. sensitivity encoding [SENSE], simultaneous acquisition of spatial harmonics [SMASH], unaliasing by Fourier encoding of the overlaps using the temporal dimension [UNFOLD], k-t-broad-use linear acquisition speed-up technique [k-t-BLAST], k-t-SENSE
-
- 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
- G01R33/565—Correction of image distortions, e.g. due to magnetic field inhomogeneities
- G01R33/56554—Correction of image distortions, e.g. due to magnetic field inhomogeneities caused by acquiring plural, differently encoded echo signals after one RF excitation, e.g. correction for readout gradients of alternating polarity in EPI
-
- 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
- G01R33/567—Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution gated by physiological signals, i.e. synchronization of acquired MR data with periodical motion of an object of interest, e.g. monitoring or triggering system for cardiac or respiratory gating
- G01R33/5676—Gating or triggering based on an MR signal, e.g. involving one or more navigator echoes for motion monitoring and correction
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computing arrangements using knowledge-based models
- G06N5/01—Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2211/00—Image generation
- G06T2211/40—Computed tomography
- G06T2211/424—Iterative
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- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- High Energy & Nuclear Physics (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Artificial Intelligence (AREA)
- Biomedical Technology (AREA)
- Biophysics (AREA)
- Molecular Biology (AREA)
- Condensed Matter Physics & Semiconductors (AREA)
- Radiology & Medical Imaging (AREA)
- Signal Processing (AREA)
- Mathematical Physics (AREA)
- Computational Linguistics (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Computing Systems (AREA)
- Evolutionary Computation (AREA)
- Data Mining & Analysis (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Medical Informatics (AREA)
- Heart & Thoracic Surgery (AREA)
- Pathology (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- Public Health (AREA)
- Veterinary Medicine (AREA)
- Magnetic Resonance Imaging Apparatus (AREA)
- Algebra (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
Applications Claiming Priority (5)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US202063022925P | 2020-05-11 | 2020-05-11 | |
| US63/022,925 | 2020-05-11 | ||
| EP20176989.0 | 2020-05-28 | ||
| EP20176989.0A EP3916417A1 (en) | 2020-05-28 | 2020-05-28 | Correction of magnetic resonance images using multiple magnetic resonance imaging system configurations |
| PCT/EP2021/060286 WO2021228515A1 (en) | 2020-05-11 | 2021-04-21 | Correction of magnetic resonance images using multiple magnetic resonance imaging system configurations |
Publications (3)
| Publication Number | Publication Date |
|---|---|
| JP2023526008A JP2023526008A (ja) | 2023-06-20 |
| JP2023526008A5 JP2023526008A5 (https=) | 2024-06-14 |
| JP7757314B2 true JP7757314B2 (ja) | 2025-10-21 |
Family
ID=70918263
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2022568522A Active JP7757314B2 (ja) | 2020-05-11 | 2021-04-21 | 複数の磁気共鳴イメージングシステム構成を使用した磁気共鳴画像の補正 |
Country Status (5)
| Country | Link |
|---|---|
| US (1) | US12067652B2 (https=) |
| EP (2) | EP3916417A1 (https=) |
| JP (1) | JP7757314B2 (https=) |
| CN (1) | CN115552272A (https=) |
| WO (1) | WO2021228515A1 (https=) |
Families Citing this family (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3828579A1 (en) * | 2019-11-28 | 2021-06-02 | Koninklijke Philips N.V. | Adaptive reconstruction of magnetic resonance images |
| US11828824B2 (en) * | 2021-03-17 | 2023-11-28 | GE Precision Healthcare LLC | System and method for deep learning-based accelerated magnetic resonance imaging with extended field of view coil sensitivity calibration |
| US12555291B2 (en) * | 2021-04-27 | 2026-02-17 | Siemens Healthineers Ag | Method for automated regularization of hybrid K-space combination using a noise adjustment scan |
| US20230337987A1 (en) * | 2022-04-21 | 2023-10-26 | The General Hospital Corporation | Detecting motion artifacts from k-space data in segmentedmagnetic resonance imaging |
| US20240037815A1 (en) * | 2022-07-26 | 2024-02-01 | Siemens Healthcare Gmbh | Method and apparatus for accelerated acquisition and reconstruction of cine mri using a deep learning based convolutional neural network |
| EP4431967A1 (en) | 2023-03-13 | 2024-09-18 | Koninklijke Philips N.V. | Training of neural networks to generate synthetic three-dimensional magnetic resonance images |
| US20250005715A1 (en) * | 2023-06-30 | 2025-01-02 | The Regents Of The University Of California | Methods, apparatuses, systems and computer-readable mediums for correcting echo planar imaging artifacts |
| US20250314728A1 (en) * | 2024-04-08 | 2025-10-09 | GE Precision Healthcare LLC | System and method for detecting motion-ridden shots in multi-shot acquisitions and utilizing deep learning based reconstruction for motion correction |
| US12372369B1 (en) * | 2024-07-11 | 2025-07-29 | SB Technology, Inc. | Detecting and fixing map artifacts |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2016209336A (ja) | 2015-05-11 | 2016-12-15 | 株式会社日立製作所 | 磁気共鳴イメージング装置 |
Family Cites Families (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2007124450A2 (en) | 2006-04-21 | 2007-11-01 | The Trustees Of The University Of Pennsylvania | Motion artifact compensation |
| US9340768B2 (en) | 2008-07-16 | 2016-05-17 | The Texas A&M University System | Transformation of glycerol and cellulosic materials into high energy fuels |
| US8848990B2 (en) | 2010-09-28 | 2014-09-30 | Siemens Aktiengesellschaft | Automatic registration of image series with varying contrast based on synthetic images derived from intensity behavior model |
| JP5835930B2 (ja) * | 2011-04-15 | 2015-12-24 | 株式会社東芝 | 医用画像表示装置 |
| US9588207B2 (en) * | 2011-10-06 | 2017-03-07 | National Institutes of Health (NIH), U.S. Dept. of Health and Human Services (DHHS), The United States of America NIH Division of Extramural Inventions and Technology Resources (DEITR) | System for reconstructing MRI images acquired in parallel |
| WO2015197366A1 (en) | 2014-06-23 | 2015-12-30 | Koninklijke Philips N.V. | Motion correction in magnetic resonance imaging |
| US9983283B2 (en) | 2015-03-16 | 2018-05-29 | Toshiba Medical Systems Corporation | Accelerated MRI using radial strips and undersampling of k-space |
| US10671939B2 (en) | 2016-04-22 | 2020-06-02 | New York University | System, method and computer-accessible medium for learning an optimized variational network for medical image reconstruction |
| 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 |
| EP3447520A1 (en) * | 2017-08-22 | 2019-02-27 | Koninklijke Philips N.V. | Data-driven correction of phase depending artefacts in a magnetic resonance imaging system |
| EP3477583A1 (en) | 2017-10-31 | 2019-05-01 | Koninklijke Philips N.V. | Deep-learning based processing of motion artifacts in magnetic resonance imaging data |
| US10573031B2 (en) | 2017-12-06 | 2020-02-25 | Siemens Healthcare Gmbh | Magnetic resonance image reconstruction with deep reinforcement learning |
| KR102708986B1 (ko) | 2018-04-19 | 2024-09-24 | 서틀 메디컬, 인크. | 딥 러닝을 사용하여 자기 공명 이미징을 향상시키기 위한 시스템들 및 방법들 |
| US12039699B2 (en) * | 2018-05-25 | 2024-07-16 | Vidur MAHAJAN | Method and system for simulating and constructing original medical images from one modality to other modality |
| US10852379B2 (en) | 2018-06-07 | 2020-12-01 | Siemens Healthcare Gmbh | Artifact reduction by image-to-image network in magnetic resonance imaging |
| US11756160B2 (en) * | 2018-07-27 | 2023-09-12 | Washington University | ML-based methods for pseudo-CT and HR MR image estimation |
| CN109325985B (zh) * | 2018-09-18 | 2020-07-21 | 上海联影智能医疗科技有限公司 | 磁共振图像重建方法、装置和计算机可读存储介质 |
| CN110095742B (zh) * | 2019-05-13 | 2022-02-08 | 上海东软医疗科技有限公司 | 一种基于神经网络的平面回波成像方法和装置 |
| CN110333466B (zh) * | 2019-06-19 | 2022-06-07 | 东软医疗系统股份有限公司 | 一种基于神经网络的磁共振成像方法和装置 |
| CN110244246B (zh) * | 2019-07-03 | 2021-07-16 | 上海联影医疗科技股份有限公司 | 磁共振成像方法、装置、计算机设备和存储介质 |
| CN110807492B (zh) * | 2019-11-06 | 2022-05-13 | 厦门大学 | 一种磁共振多参数同时定量成像方法及系统 |
| CN110942496B (zh) * | 2019-12-13 | 2022-02-11 | 厦门大学 | 基于螺旋桨采样和神经网络的磁共振图像重建方法及系统 |
-
2020
- 2020-05-28 EP EP20176989.0A patent/EP3916417A1/en not_active Withdrawn
-
2021
- 2021-04-21 EP EP21719164.2A patent/EP4150360A1/en active Pending
- 2021-04-21 JP JP2022568522A patent/JP7757314B2/ja active Active
- 2021-04-21 WO PCT/EP2021/060286 patent/WO2021228515A1/en not_active Ceased
- 2021-04-21 CN CN202180034897.8A patent/CN115552272A/zh active Pending
- 2021-04-21 US US17/923,617 patent/US12067652B2/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2016209336A (ja) | 2015-05-11 | 2016-12-15 | 株式会社日立製作所 | 磁気共鳴イメージング装置 |
Non-Patent Citations (1)
| Title |
|---|
| Blake E. Dewey, et al.,DeepHarmony: A deep learning approach to contrast harmonization across scanner changes,Magn Reson Imaging,2019年,64,160-170 |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2021228515A1 (en) | 2021-11-18 |
| US12067652B2 (en) | 2024-08-20 |
| JP2023526008A (ja) | 2023-06-20 |
| EP3916417A1 (en) | 2021-12-01 |
| US20230186532A1 (en) | 2023-06-15 |
| EP4150360A1 (en) | 2023-03-22 |
| CN115552272A (zh) | 2022-12-30 |
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