CN113939846B - 具有偏共振伪影校正的螺旋mr成像 - Google Patents
具有偏共振伪影校正的螺旋mr成像 Download PDFInfo
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- CN113939846B CN113939846B CN202080041174.6A CN202080041174A CN113939846B CN 113939846 B CN113939846 B CN 113939846B CN 202080041174 A CN202080041174 A CN 202080041174A CN 113939846 B CN113939846 B CN 113939846B
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/80—Geometric correction
-
- 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
- G01R33/4824—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 using a non-Cartesian trajectory
-
- 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
- G01R33/56563—Correction of image distortions, e.g. due to magnetic field inhomogeneities caused by a distortion of the main magnetic field B0, e.g. temporal variation of the magnitude or spatial inhomogeneity of B0
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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
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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
-
- 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
-
- 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
- G01R33/56536—Correction of image distortions, e.g. due to magnetic field inhomogeneities due to magnetic susceptibility variations
-
- 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
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- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Condensed Matter Physics & Semiconductors (AREA)
- High Energy & Nuclear Physics (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Signal Processing (AREA)
- Radiology & Medical Imaging (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Biophysics (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Molecular Biology (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Evolutionary Computation (AREA)
- Data Mining & Analysis (AREA)
- Computational Linguistics (AREA)
- Biomedical Technology (AREA)
- Artificial Intelligence (AREA)
- Life Sciences & Earth Sciences (AREA)
- Magnetic Resonance Imaging Apparatus (AREA)
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| EP19178061.8 | 2019-06-04 | ||
| EP19178061.8A EP3748384A1 (en) | 2019-06-04 | 2019-06-04 | Spiral mr imaging with off-resonance artefact correction |
| PCT/EP2020/065273 WO2020245144A1 (en) | 2019-06-04 | 2020-06-03 | Spiral mr imaging with off-resonance artefact correction |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113939846A CN113939846A (zh) | 2022-01-14 |
| CN113939846B true CN113939846B (zh) | 2025-06-17 |
Family
ID=66751971
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202080041174.6A Active CN113939846B (zh) | 2019-06-04 | 2020-06-03 | 具有偏共振伪影校正的螺旋mr成像 |
Country Status (5)
| Country | Link |
|---|---|
| US (1) | US11867784B2 (enExample) |
| EP (2) | EP3748384A1 (enExample) |
| JP (1) | JP7507793B2 (enExample) |
| CN (1) | CN113939846B (enExample) |
| WO (1) | WO2020245144A1 (enExample) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2023038799A (ja) * | 2021-09-07 | 2023-03-17 | キヤノンメディカルシステムズ株式会社 | データ処理装置、磁気共鳴イメージング装置及びデータ処理方法 |
| CN115187449A (zh) * | 2022-06-20 | 2022-10-14 | 湖南大学 | 一种基于透视变换的提高对抗样本迁移性的方法 |
| CN115327459B (zh) * | 2022-08-18 | 2025-10-17 | 深圳市联影高端医疗装备创新研究院 | 一种并行发射局部激发脉冲生成方法、装置和存储介质 |
| CN118549870B (zh) * | 2024-06-20 | 2025-11-07 | 厦门大学 | 多扫描磁共振图像的流动伪影校正方法及系统 |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108132274A (zh) * | 2017-12-21 | 2018-06-08 | 厦门大学 | 不均匀磁场下回波平面成像无参考扫描图像畸变矫正方法 |
| CN109242924A (zh) * | 2018-08-31 | 2019-01-18 | 南方医科大学 | 一种基于深度学习的核磁共振图像的降采样伪影去除方法 |
Family Cites Families (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5617028A (en) * | 1995-03-09 | 1997-04-01 | Board Of Trustees Of The Leland Stanford Junior University | Magnetic field inhomogeneity correction in MRI using estimated linear magnetic field map |
| WO2004086060A2 (en) | 2003-03-20 | 2004-10-07 | Case Western Reserve University | Chemical species suppression for mri imaging using spiral trajectories with off-resonance correction |
| WO2005003805A1 (en) | 2003-06-27 | 2005-01-13 | Case Western University | Efficient method for mr image reconstruction using coil sensitivity encoding |
| CN1327809C (zh) * | 2005-03-28 | 2007-07-25 | 南方医科大学 | 在t1加权磁共振成像中用propeller采样方式消除运动伪影的方法 |
| US7642777B1 (en) | 2006-08-21 | 2010-01-05 | University Of Virginia Patent Foundation | Fast automatic linear off-resonance correction method for spiral imaging |
| US8238634B1 (en) | 2007-02-23 | 2012-08-07 | University Of Virginia Patent Foundation | Efficient off-resonance correction method and system for spiral imaging with improved accuracy |
| DE102008007048B4 (de) * | 2008-01-31 | 2010-06-17 | Siemens Aktiengesellschaft | Dynamische Verzeichnungskorrektur bei EPI-Messungen in der medizinischen Magnet-Resonanz-Bildgebung |
| US9322896B2 (en) | 2012-04-20 | 2016-04-26 | University Of Virginia Patent Foundation | Systems and methods for reduced off-resonance blurring in spiral imaging |
| CN104603629B (zh) | 2012-09-04 | 2017-06-13 | 皇家飞利浦有限公司 | 具有狄克逊水脂分离的propeller |
| US9964615B2 (en) * | 2013-03-21 | 2018-05-08 | Koninklijke Philips N.V. | MR image reconstruction using compressed sensing |
| WO2017009391A1 (en) * | 2015-07-15 | 2017-01-19 | Koninklijke Philips N.V. | Mr imaging with motion detection |
| JP6568760B2 (ja) | 2015-09-30 | 2019-08-28 | 株式会社日立製作所 | 磁気共鳴イメージング装置、および、画像処理装置 |
| US10489907B2 (en) | 2017-11-13 | 2019-11-26 | Siemens Healthcare Gmbh | Artifact identification and/or correction for medical imaging |
| CN107945132B (zh) * | 2017-11-29 | 2022-10-04 | 深圳安科高技术股份有限公司 | 一种基于神经网络的ct图像的伪影校正方法及装置 |
| 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 |
| US10915990B2 (en) * | 2018-10-18 | 2021-02-09 | General Electric Company | Systems and methods for denoising medical images with deep learning network |
| CN109741409A (zh) * | 2018-11-30 | 2019-05-10 | 厦门大学 | 回波平面成像涡流伪影的无参考扫描校正方法 |
-
2019
- 2019-06-04 EP EP19178061.8A patent/EP3748384A1/en not_active Withdrawn
-
2020
- 2020-06-03 WO PCT/EP2020/065273 patent/WO2020245144A1/en not_active Ceased
- 2020-06-03 US US17/614,595 patent/US11867784B2/en active Active
- 2020-06-03 JP JP2021571885A patent/JP7507793B2/ja active Active
- 2020-06-03 EP EP20729749.0A patent/EP3980801B1/en active Active
- 2020-06-03 CN CN202080041174.6A patent/CN113939846B/zh active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108132274A (zh) * | 2017-12-21 | 2018-06-08 | 厦门大学 | 不均匀磁场下回波平面成像无参考扫描图像畸变矫正方法 |
| CN109242924A (zh) * | 2018-08-31 | 2019-01-18 | 南方医科大学 | 一种基于深度学习的核磁共振图像的降采样伪影去除方法 |
Also Published As
| Publication number | Publication date |
|---|---|
| US20220229134A1 (en) | 2022-07-21 |
| JP2022535548A (ja) | 2022-08-09 |
| EP3980801A1 (en) | 2022-04-13 |
| EP3980801B1 (en) | 2024-09-04 |
| US11867784B2 (en) | 2024-01-09 |
| EP3748384A1 (en) | 2020-12-09 |
| JP7507793B2 (ja) | 2024-06-28 |
| CN113939846A (zh) | 2022-01-14 |
| WO2020245144A1 (en) | 2020-12-10 |
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