Development of fast imaging techniques in MRI From the principle to the recent development

Similar documents
K-Space Trajectories and Spiral Scan

G Practical Magnetic Resonance Imaging II Sackler Institute of Biomedical Sciences New York University School of Medicine. Compressed Sensing

MRI Physics II: Gradients, Imaging

Compressed Sensing for Rapid MR Imaging

Fast Imaging Trajectories: Non-Cartesian Sampling (1)

Image reconstruction using compressed sensing for individual and collective coil methods.

Accelerated MRI Techniques: Basics of Parallel Imaging and Compressed Sensing

Supplemental Material for Efficient MR Image Reconstruction for Compressed MR Imaging

Spread Spectrum Using Chirp Modulated RF Pulses for Incoherent Sampling Compressive Sensing MRI

Role of Parallel Imaging in High Field Functional MRI

Combination of Parallel Imaging and Compressed Sensing for high acceleration factor at 7T

Accelerated parameter mapping with compressed sensing: an alternative to MR fingerprinting

Sparse sampling in MRI: From basic theory to clinical application. R. Marc Lebel, PhD Department of Electrical Engineering Department of Radiology

Accelerated MRI by SPEED with Generalized Sampling Schemes

Use of Multicoil Arrays for Separation of Signal from Multiple Slices Simultaneously Excited

Joint SENSE Reconstruction for Faster Multi-Contrast Wave Encoding

Controlled Aliasing in Volumetric Parallel Imaging (2D CAIPIRINHA)

Improving the quality of compressed sensing MRI that exploits adjacent slice similarity

Using learned under-sampling pattern for increasing speed of cardiac cine MRI based on compressive sensing principles

Parallel Imaging. Marcin.

Sampling, Ordering, Interleaving

Module 4. K-Space Symmetry. Review. K-Space Review. K-Space Symmetry. Partial or Fractional Echo. Half or Partial Fourier HASTE

Compressed Sensing MRI with Multichannel Data Using Multicore Processors

Weighted-CS for reconstruction of highly under-sampled dynamic MRI sequences

PERFORMANCE ANALYSIS BETWEEN TWO SPARSITY-CONSTRAINED MRI METHODS: HIGHLY CONSTRAINED BACKPROJECTION (HYPR) AND

Fast Dynamic MRI for Radiotherapy

MRI. When to use What sequences. Outline 2012/09/19. Sequence: Definition. Basic Principles: Step 2. Basic Principles: Step 1. Govind Chavhan, MD

Compressed Sensing Reconstructions for Dynamic Contrast Enhanced MRI

Separate Magnitude and Phase Regularization via Compressed Sensing

Dynamic Autocalibrated Parallel Imaging Using Temporal GRAPPA (TGRAPPA)

On the Temporal Fidelity of Nonlinear Inverse Reconstructions for Real- Time MRI The Motion Challenge

2D spatially selective excitation pulse design and the artifact evaluation

MR-Encephalography (MREG)

Compressed Sensing MRI. [A look at how CS can improve on current imaging techniques] Digital Object Identifier /MSP.2007.

Real-time MRI at a resolution of 20 ms

Advanced Imaging Trajectories

A Convex Optimization Approach to pmri Reconstruction

Spatially selective RF excitation using k-space analysis

VD-AUTO-SMASH Imaging

Accelerated Aortic Flow Assessment with Compressed Sensing with and without Use of the Sparsity of the Complex Difference Image

Zigzag Sampling for Improved Parallel Imaging

Automatic Correction of Echo-Planar Imaging (EPI) Ghosting Artifacts in Real-Time Interactive Cardiac MRI Using Sensitivity Encoding

A practical acceleration algorithm for real-time imaging

EE290T: Advanced Reconstruction Methods for Magnetic Resonance Imaging. Martin Uecker

Constrained Reconstruction of Sparse Cardiac MR DTI Data

NIH Public Access Author Manuscript Med Phys. Author manuscript; available in PMC 2009 March 13.

Sampling, Ordering, Interleaving

Fast reconstruction for multichannel compressed sensing using a hierarchically semiseparable solver

Collaborative Sparsity and Compressive MRI

Image Denoising for Metal MRI Exploiting Sparsity and Low Rank Priors

A Rapid and Robust Numerical Algorithm for Sensitivity Encoding with Sparsity Constraints: Self-Feeding Sparse SENSE

A model-based method with joint sparsity constant for direct diffusion tensor estimation. Zhu, Y; Wu, Y; Zheng, YJ; Wu, EX; Ying, L; Liang, D

29 th NATIONAL RADIO SCIENCE CONFERENCE (NRSC 2012) April 10 12, 2012, Faculty of Engineering/Cairo University, Egypt

EE290T: Advanced Reconstruction Methods for Magnetic Resonance Imaging. Martin Uecker

Module 5: Dynamic Imaging and Phase Sharing. (true-fisp, TRICKS, CAPR, DISTAL, DISCO, HYPR) Review. Improving Temporal Resolution.

Fast Cardiac CINE MRI by Iterative Truncation of Small Transformed Coefficients

MEDICAL IMAGE ANALYSIS

(a Scrhon5 R2iwd b. P)jc%z 5. ivcr3. 1. I. ZOms Xn,s. 1E IDrAS boms. EE225E/BIOE265 Spring 2013 Principles of MRI. Assignment 8 Solutions

The cost of parallel imaging in functional MRI of the human brain

Accelerated 4D flow MRI

MRI reconstruction from partial k-space data by iterative stationary wavelet transform thresholding

Fast Implementation of Iterative Image Reconstruction

Evaluations of k-space Trajectories for Fast MR Imaging for project of the course EE591, Fall 2004

High dynamic range magnetic resonance flow imaging in the abdomen

Tradeoffs and complexities in model-based MR image reconstruction

Steen Moeller Center for Magnetic Resonance research University of Minnesota

A Novel Iterative Thresholding Algorithm for Compressed Sensing Reconstruction of Quantitative MRI Parameters from Insufficient Data

arxiv: v2 [physics.med-ph] 3 Aug 2017

Sources of Distortion in Functional MRI Data

Partially Parallel Imaging With Localized Sensitivities (PILS)

Improved Spatial Localization in 3D MRSI with a Sequence Combining PSF-Choice, EPSI and a Resolution Enhancement Algorithm

Learning a Spatiotemporal Dictionary for Magnetic Resonance Fingerprinting with Compressed Sensing

Generalized Autocalibrating Partially Parallel Acquisitions (GRAPPA)

Fast Reconstruction for Multichannel Compressed Sensing Using a Hierarchically Semiseparable Solver

Spiral keyhole imaging for MR fingerprinting

Non-Iterative Reconstruction with a Prior for Undersampled Radial MRI Data

Sparse MRI: The Application of Compressed Sensing for Rapid MR Imaging

Optimal Sampling Geometries for TV-Norm Reconstruction of fmri Data

Blind Sparse Motion MRI with Linear Subpixel Interpolation

Cardiac diffusion tensor imaging based on compressed sensing using joint sparsity and low-rank approximation

Computational Acceleration for MR Image Reconstruction in Partially Parallel Imaging Xiaojing Ye*, Yunmei Chen, and Feng Huang

Automated Aperture GenerationQuantitative Evaluation of Ape

surface Image reconstruction: 2D Fourier Transform

k-space Interpretation of the Rose Model: Noise Limitation on the Detectable Resolution in MRI

Fast, Iterative Image Reconstruction for MRI in the Presence of Field Inhomogeneities

Magnetic Resonance Angiography

TOPICS 2/5/2006 8:17 PM. 2D Acquisition 3D Acquisition

Midterm Review

Deconvolution with curvelet-domain sparsity Vishal Kumar, EOS-UBC and Felix J. Herrmann, EOS-UBC

Accelerating Cardiac Cine 3D Imaging Using k-t BLAST

Faster 3D Vocal Tract Real-time MRI Using Constrained Reconstruction

M R I Physics Course

Controlled Aliasing in Parallel Imaging Results in Higher Acceleration (CAIPIRINHA)

2/5/2006 8:26 PM TOPICS

Fast methods for magnetic resonance angiography (MRA)

Dynamic Contrast enhanced MRA

arxiv: v2 [physics.med-ph] 22 Jul 2014

MultiSlice CAIPIRINHA Using View Angle Tilting Technique (CAIPIVAT)

Radial k-t FOCUSS for High-Resolution Cardiac Cine MRI

Regularized Sensitivity Encoding (SENSE) Reconstruction Using Bregman Iterations

Transcription:

980-8575 2-1 2012 10 13 Development of fast imaging techniques in MRI From the principle to the recent development Yoshio MACHIDA and Issei MORI Health Sciences, Tohoku University Graduate School of Medicine 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan Received on October 13, 2012 Abstract : The purpose of this paper is to review the development of fast imaging techniques in MRI. After the brief introduction of the principle of Fourier transform MRI, conventional fast imaging techniques mainly based on the improvement of pulse sequences are described. Next, further fast imaging techniques such as parallel imaging, k-t imaging technique, and finally, recently developed compressed sensingcsmri techniques are discussed. Key words : Fourier transform MRI, fast imaging, pulse sequence, parallel imaging, compressed sensing MRI MRI MRI 2012 5 International Society for Magnetic Resonance in Medicine: ISMRM Compressed Sensing : CS MR CS-MRI CS-MRI MRI MRI k MR 2 3 k CartesianRadial Spiral k [2-4] k k CS-MRI MRI 2 MR Lauterbur 1973 a [1] x, y k kx, ky Fig.1 MR 7

Fig.3 Fig.2 k [5]1-2-1 MRI 1970 MRI [6]1980 MRI 80 90 [7] 2 MRI 2 3 k k 1980 Gradient Echo : GRE FLASH [8] 10 3 90 MR MRA3 [9] 1977Mansfield EPIEcho Planar Imaging[6] EPI EPI Fast Spin Echo: FSE RARE TrueFISP balanced SSFP : bssfp 90 RF SNR PI PI 90 90 SMASH SENSE [10] PI k PI 3 Fig.4 8

2000 RF 3 k t k-t k [11] A L1 b CS y 0 K c x0 M N [12] A A A A A yax L1 M N A MRI CS MRI MR MRI CS-MRI [12, 13] CS yax A MR Lustig CS [14, 15]MRA T1 T2 Wavelet Lustig MRI k L1 3 k MRI CS 2012 ISMRM d 1MRI yaxaγfts S FT Γ Fig.5 arg min x 1 subj.to yax x k-t MRI 2 k-t 9

k-t p k-p N MRI MRI CS 3CS MRI Lagrangian form minmize yax 2λ1 x 1λ2TVx A 1 2 e 3 Total Valiation : TV λ1λ2 CS-MRI CS CS 3 MRI k Wavelet t k TeFSE [16] CS-MRI 3 CS-MRI CS A A Γ FTS 1 CS 3 k Lustig f CS CS MRI CS-MRI Lustig JSPS 24591747 [ 1 ] Lauterbur PC : Image Formation by Induced Local Interactions : Examples Employing Nuclear Magnetic Resonance, Nature 242, 190-191, 1973. [ 2 ] Bernstein MA, King KF, Zhou Xj : Handbook of MRI pulse sequences, Elsevier academic press, 2004. [ 3 ] MRI 2 Fig.6 3 10

Fig.7 MR k d TV Lustig 2010 [ 4 ] CT MRI 2010 [ 5 ] Moran PR : A flow velocity zeugmatographic interlace for NMR imaging in humans, Magn Reson Imaging, 1, 197-203, 1982. [ 6 ] Mansfield P : Multi-planar image formation using NMR spin echoes, J. Phys. C : Solid State Phys., 10, L55-L58, 1977. [ 7 ] MRIJpn. J. Med. Phys Vol.304p.155-1612011 [ 8 ] Haase A, Frahm J, Matthaei D, et al. : FLASH Imaging. Rapid NMR Imaging Using Low Flip-Angle Pulses, J. Magn. Reson., 67, 258-266, 1986. [ 9 ] Laub, GA,. Kaiser, WA. : MR angiography with gradient moment refocusing, J. Comput Assist Tomogr, 12, 377, 1988. [10] Pruessmann KP, Weiger M, Scheidegger MB, et al.: SENSE: sensitivity encoding for fast MRI, Magn. Reson. Med., 42, 952-962, 1999. [11] Tsao J, Boesiger P, Pruessmann KP : k-t BLAST and k-t SENSE : Dynamic MRI with high frame rate exploiting spatiotemporal correlations, Magn. Reson. Med., 50, 1031-1042, 2003. [12] IEICE Fundamental Review4139-472010 [13] 17263-692010 [14] Lustig M, Donoho D, Pauly JM. : Sparse MRI : The Application of Compressed Sensing for Rapid MR Imaging, Magn Reson Med 58, 1182-1195, 2007. [15] Lustig M, Donoho D, Santos JM, Pauly JM : Compressed Sensing MRI, IEEE Signal Processing Magazine, 252, 72-82, Mar. 2008. [16] Sumpf TJ, Uecker M, Boretius S, Frahm J. : Model-based nonlinear inverse reconstruction for T2 mapping using highly undersampled spin-echo MRI, J. Magn. Reson. Imaging, 34, 420-428, 2011. a MansfieldEPI 2003 b L1 x 1 xi L1 L1 c K dkozerke S. Parallel acquisition & compressed sensing / Temporal & parametric undersampling strategies, in Proc. Intl. Soc. Mag. Reson. Med. 202012,weekend education program e Wavelet Wavelet 4.4 f Lustig M, SparseMRI V0.2http://www.stanford.edu/ mlustig/ SparseMRI.html 11