JP2023548854A - 磁気共鳴イメージングにおける高周波パルス及び勾配パルスのリアルタイム設計 - Google Patents

磁気共鳴イメージングにおける高周波パルス及び勾配パルスのリアルタイム設計 Download PDF

Info

Publication number
JP2023548854A
JP2023548854A JP2023526956A JP2023526956A JP2023548854A JP 2023548854 A JP2023548854 A JP 2023548854A JP 2023526956 A JP2023526956 A JP 2023526956A JP 2023526956 A JP2023526956 A JP 2023526956A JP 2023548854 A JP2023548854 A JP 2023548854A
Authority
JP
Japan
Prior art keywords
neural network
convolutional neural
magnetic resonance
spatially selective
gradient pulse
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
JP2023526956A
Other languages
English (en)
Japanese (ja)
Other versions
JP2023548854A5 (https=
Inventor
ヤージン チャン
ジャズン ワン
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Koninklijke Philips NV
Original Assignee
Koninklijke Philips NV
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Koninklijke Philips NV filed Critical Koninklijke Philips NV
Publication of JP2023548854A publication Critical patent/JP2023548854A/ja
Publication of JP2023548854A5 publication Critical patent/JP2023548854A5/ja
Pending legal-status Critical Current

Links

Images

Classifications

    • 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
    • G01R33/483—NMR imaging systems with selection of signals or spectra from particular regions of the volume, e.g. in vivo spectroscopy
    • G01R33/4833—NMR imaging systems with selection of signals or spectra from particular regions of the volume, e.g. in vivo spectroscopy using spatially selective excitation of the volume of interest, e.g. selecting non-orthogonal or inclined slices
    • G01R33/4836—NMR imaging systems with selection of signals or spectra from particular regions of the volume, e.g. in vivo spectroscopy using spatially selective excitation of the volume of interest, e.g. selecting non-orthogonal or inclined slices using an RF pulse being spatially selective in more than one spatial dimension, e.g. a 2D pencil-beam excitation pulse
    • 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
    • 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
    • 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

Landscapes

  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Condensed Matter Physics & Semiconductors (AREA)
  • High Energy & Nuclear Physics (AREA)
  • Computing Systems (AREA)
  • Biomedical Technology (AREA)
  • Molecular Biology (AREA)
  • Data Mining & Analysis (AREA)
  • General Engineering & Computer Science (AREA)
  • Computational Linguistics (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Biophysics (AREA)
  • Evolutionary Computation (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Signal Processing (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Optics & Photonics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Radiology & Medical Imaging (AREA)
  • Magnetic Resonance Imaging Apparatus (AREA)
JP2023526956A 2020-11-04 2021-11-04 磁気共鳴イメージングにおける高周波パルス及び勾配パルスのリアルタイム設計 Pending JP2023548854A (ja)

Applications Claiming Priority (5)

Application Number Priority Date Filing Date Title
CNPCT/CN2020/126499 2020-11-04
CN2020126499 2020-11-04
EP20214200.6 2020-12-15
EP20214200.6A EP3995848A1 (en) 2020-11-04 2020-12-15 Realtime design of radio-frequency pulses and gradient pulses in magnetic resonanc imaging
PCT/EP2021/080567 WO2022096539A1 (en) 2020-11-04 2021-11-04 Realtime design of radio-frequency pulses and gradient pulses in magnetic resonanc imaging

Publications (2)

Publication Number Publication Date
JP2023548854A true JP2023548854A (ja) 2023-11-21
JP2023548854A5 JP2023548854A5 (https=) 2024-11-08

Family

ID=81000614

Family Applications (1)

Application Number Title Priority Date Filing Date
JP2023526956A Pending JP2023548854A (ja) 2020-11-04 2021-11-04 磁気共鳴イメージングにおける高周波パルス及び勾配パルスのリアルタイム設計

Country Status (6)

Country Link
US (1) US12360190B2 (https=)
EP (1) EP3995848A1 (https=)
JP (1) JP2023548854A (https=)
CN (1) CN116406463A (https=)
DE (1) DE112021005801T5 (https=)
WO (1) WO2022096539A1 (https=)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US12387096B2 (en) * 2021-10-06 2025-08-12 Google Llc Image-to-image mapping by iterative de-noising
CN115759179B (zh) * 2022-11-18 2026-03-03 中国科学院自动化研究所 一种应用于多任务学习的策略模型训练方法、装置及设备
WO2026006649A1 (en) * 2024-06-27 2026-01-02 The General Hospital Corporation System and method of creating and using automated system for physics control

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2001095773A (ja) * 1999-09-28 2001-04-10 Hitachi Medical Corp 磁気共鳴画像診断装置
JP2008054738A (ja) * 2006-08-29 2008-03-13 Hitachi Medical Corp 磁気共鳴イメージング装置
JP2016154849A (ja) * 2015-02-23 2016-09-01 東芝メディカルシステムズ株式会社 磁気共鳴イメージング装置
JP2016171847A (ja) * 2015-03-16 2016-09-29 東芝メディカルシステムズ株式会社 Ｍｒｉ装置
US20190086488A1 (en) * 2017-09-15 2019-03-21 Siemens Healthcare Gmbh Magnetic Resonance Radio Frequency Pulse Design using Machine Learning

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10588523B2 (en) * 2016-04-15 2020-03-17 Siemens Healthcare Gmbh 4D flow measurements of the hepatic vasculatures with two-dimensional excitation
CN106372571A (zh) * 2016-08-18 2017-02-01 宁波傲视智绘光电科技有限公司 路面交通标志检测与识别方法
EP3581955A1 (en) * 2018-06-12 2019-12-18 Koninklijke Philips N.V. Determination of higher order terms of the three-dimensional impulse response function of the magnetic field gradient system of a magnetic resonance imaging system
JP2022526718A (ja) * 2019-03-14 2022-05-26 ハイパーファイン，インコーポレイテッド 空間周波数データから磁気共鳴画像を生成するための深層学習技術
US11221384B2 (en) * 2019-04-29 2022-01-11 Regents Of The University Of Minnesota System and method for producing radiofrequency pulses in magnetic resonance using an optimal phase surface

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2001095773A (ja) * 1999-09-28 2001-04-10 Hitachi Medical Corp 磁気共鳴画像診断装置
JP2008054738A (ja) * 2006-08-29 2008-03-13 Hitachi Medical Corp 磁気共鳴イメージング装置
JP2016154849A (ja) * 2015-02-23 2016-09-01 東芝メディカルシステムズ株式会社 磁気共鳴イメージング装置
JP2016171847A (ja) * 2015-03-16 2016-09-29 東芝メディカルシステムズ株式会社 Ｍｒｉ装置
US20190086488A1 (en) * 2017-09-15 2019-03-21 Siemens Healthcare Gmbh Magnetic Resonance Radio Frequency Pulse Design using Machine Learning

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
TIANRUI LUO ET AL.: ""Joint Design of RF and gradient waveforms via auto-differentiation for 3D tailored exciteation in M", [ONLINE], JPN6025029553, 24 August 2020 (2020-08-24), pages 2008 - 10594, ISSN: 0005646076 *

Also Published As

Publication number Publication date
US20230408612A1 (en) 2023-12-21
WO2022096539A1 (en) 2022-05-12
EP3995848A1 (en) 2022-05-11
DE112021005801T5 (de) 2023-10-05
US12360190B2 (en) 2025-07-15
CN116406463A (zh) 2023-07-07

Similar Documents

Publication Publication Date Title
EP4266074A1 (en) Segmentation of medical images reconstructed from a set of magnetic resonance images
JP7420802B2 (ja) 磁気共鳴イメージングにおける他の処理ロケーションの決定
US10353023B2 (en) Calculating MRI RF coil sensitivities using interpolation into an enlarged field of view
CN111263896B (zh) 在磁共振成像系统中对相位相关的伪影的数据驱动的校正
JP7437397B2 (ja) 球状ニューラルネットワークを用いた拡散磁気共鳴撮像
JP2023548854A (ja) 磁気共鳴イメージングにおける高周波パルス及び勾配パルスのリアルタイム設計
CN107110938A (zh) 使用具有额外180度rf脉冲的自旋回波脉冲序列的磁共振指纹
CN108431624B (zh) 定量磁化率映射磁共振图像的分割
US9320918B2 (en) Modular processing of magnetic resonance data
WO2015140277A1 (en) Control of magnetic resonance imaging acquisition using modeling
CN115427829A (zh) 减少磁共振成像中的偏离共振效应
US10591563B2 (en) Magnetic resonance imaging apparatus
CN118103721A (zh) 使用低分辨磁共振图像的运动校正
CN108896940A (zh) 用于补偿mri的梯度脉冲的系统和方法
JP2022518616A (ja) 多重拡散強調ｍｒ画像を用いたｂ０画像の計算
JP7442545B2 (ja) シミュレーション磁気共鳴画像を使用した磁気共鳴画像の補正
EP4318015A1 (en) Mri denoising using specified noise profiles
JP7638279B2 (ja) 磁気共鳴画像の適応再構成
EP4530656A1 (en) Determining readout directions and a phase encoding directions for parallel magnetic resonance imaging
EP4306983A1 (en) Making anatomical measurements using magnetic resonance imaging
EP4653904A1 (en) Removal of free induction decay artifacts in turbo spin echo mri images
EP4517648A1 (en) Oblique multiplanar reconstruction of three-dimensional medical images
EP4707843A1 (en) Improving image quality in motion corrected magnetic resonance imaging

Legal Events

Date Code Title Description
A521 Request for written amendment filed

Free format text: JAPANESE INTERMEDIATE CODE: A523

Effective date: 20241030

A621 Written request for application examination

Free format text: JAPANESE INTERMEDIATE CODE: A621

Effective date: 20241030

A977 Report on retrieval

Free format text: JAPANESE INTERMEDIATE CODE: A971007

Effective date: 20250620

A131 Notification of reasons for refusal

Free format text: JAPANESE INTERMEDIATE CODE: A131

Effective date: 20250722

A521 Request for written amendment filed

Free format text: JAPANESE INTERMEDIATE CODE: A523

Effective date: 20250917

A02 Decision of refusal

Free format text: JAPANESE INTERMEDIATE CODE: A02

Effective date: 20251222

A521 Request for written amendment filed

Free format text: JAPANESE INTERMEDIATE CODE: A523

Effective date: 20260209