The sparsity which is implicit in MR images is exploited to significantly undersample k -space. Some MR images such as angiograms are already sparse in the pixel representation; other, more complicated images have a sparse representation in some transform domain–for example, in terms of spatial finite-differences or their wavelet coefficients. According to the recently developed mathematical theory of compressedsensing, images with a sparse representation can be recovered from randomly undersampled k -space data, provided an appropriate nonlinear recovery scheme is used. Intuitively, artifacts due to random undersampling add as noise-like interference. In the sparse transform domain the significant coefficients stand out above the interference. A nonlinear thresholding scheme can recover the sparse coefficients, effectively recovering the image itself. In this article, practical incoherent undersampling schemes are developed and analyzed by means of their aliasing interference. Incoherence is introduced by pseudo-random variable-density undersampling of phase-encodes. The reconstruction is performed by minimizing the 1 norm of a transformed image, subject to data

/pdf/sparse-mri-the-application-of-compressed-sensing-for-rapid-3533njds12.pdf

Sparse MRI: The application of compressed sensing for rapid MR imaging.

Prospective Cohort Study

“Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告

Review of recent research on hepatitis C therapy for 54th annual meeting of the American association for the study of liver diseases

This article reviews the requirements for successful compressed sensing (CS), describes their natural fit to MRI, and gives examples of four interesting applications of CS in MRI. The authors emphasize on an intuitive understanding of CS by describing the CS reconstruction as a process of interference cancellation. There is also an emphasis on the understanding of the driving factors in applications, including limitations imposed by MRI hardware, by the characteristics of different types of images, and by clinical concerns.

/pdf/compressed-sensing-mri-2wgw41cvre.pdf

Compressed Sensing MRI

OBJECTIVE. The purpose of this article is to review some of the basic principles of imaging and how metal-induced susceptibility artifacts originate in MR images. We will describe common ways to reduce or modify artifacts using readily available imaging techniques, and we will discuss some advanced methods to correct readout-direction and slice-direction artifacts. CONCLUSION. The presence of metallic implants in MRI can cause substantial image artifacts, including signal loss, failure of fat suppression, geometric distortion, and bright pile-up artifacts. These cause large resonant frequency changes and failure of many MRI mechanisms. Careful parameter and pulse sequence selections can avoid or reduce artifacts, although more advanced imaging methods offer further imaging improvements.

/pdf/metal-induced-artifacts-in-mri-196clx55op.pdf

Metal-Induced Artifacts in MRI

Magnetic resonance imaging (MRI) near metallic implants remains an unmet need because of severe artifacts, which mainly stem from large metal-induced field inhomogeneities. This work addresses MRI near metallic implants with an innovative imaging technique called "Slice Encoding for Metal Artifact Correction" (SEMAC). The SEMAC technique corrects metal artifacts via robust encoding of each excited slice against metal-induced field inhomogeneities. The robust slice encoding is achieved by extending a view-angle-tilting (VAT) spin-echo sequence with additional z-phase encoding. Although the VAT compensation gradient suppresses most in-plane distortions, the z-phase encoding fully resolves distorted excitation profiles that cause through-plane distortions. By positioning all spins in a region-of-interest to their actual spatial locations, the through-plane distortions can be corrected by summing up the resolved spins in each voxel. The SEMAC technique does not require additional hardware and can be deployed to the large installed base of whole-body MRI systems. The efficacy of the SEMAC technique in eliminating metal-induced distortions with feasible scan times is validated in phantom and in vivo spine and knee studies.

/pdf/semac-slice-encoding-for-metal-artifact-correction-in-mri-2zqm5s6j74.pdf

SEMAC: Slice Encoding for Metal Artifact Correction in MRI

Purpose
To combine gradient-echo (GRE) imaging with a multipoint water–fat separation method known as “iterative decomposition of water and fat with echo asymmetry and least squares estimation” (IDEAL) for uniform water–fat separation. Robust fat suppression is necessary for many GRE imaging applications; unfortunately, uniform fat suppression is challenging in the presence of B0 inhomogeneities. These challenges are addressed with the IDEAL technique.

Materials and Methods
Echo shifts for three-point IDEAL were chosen to optimize noise performance of the water–fat estimation, which is dependent on the relative proportion of water and fat within a voxel. Phantom experiments were performed to validate theoretical SNR predictions. Theoretical echo combinations that maximize noise performance are discussed, and examples of clinical applications at 1.5T and 3.0T are shown.

Results
The measured SNR performance validated theoretical predictions and demonstrated improved image quality compared to unoptimized echo combinations. Clinical examples of the liver, breast, heart, knee, and ankle are shown, including the combination of IDEAL with parallel imaging. Excellent water–fat separation was achieved in all cases. The utility of recombining water and fat images into “in-phase,” “out-of-phase,” and “fat signal fraction” images is also discussed.

Conclusion
IDEAL-SPGR provides robust water–fat separation with optimized SNR performance at both 1.5T and 3.0T with multicoil acquisitions and parallel imaging in multiple regions of the body. J. Magn. Reson. Imaging 2007;25:644–652. © 2007 Wiley-Liss, Inc.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jmri.20831

Water-fat separation with IDEAL gradient-echo imaging.

The 3D Cones k-space trajectory has many desirable properties for rapid and ultra-short echo time magnetic resonance imaging. An algorithm is presented that generates the 3D Cones gradient waveforms given a desired field of view and resolution. The algorithm enables a favorable trade-off between increases in readout time and decreases in the total number of required readouts. The resulting trajectory is very signal-to-noise ratio (SNR) efficient and has excellent aliasing properties. A rapid high-resolution ultra-short echo time imaging sequence is used to compare the 3D Cones trajectory to 3D projection reconstruction (3DPR) sampling schemes. For equivalent scan times, the 3D Cones trajectory has better SNR performance and fewer aliasing artifacts as compared to the 3DPR trajectory.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrm.20796

Design and analysis of a practical 3D cones trajectory.

We used a combination of parallel imaging and compressed sensing to generate images at acceleration factors that were more than double those used in our standard clinical practice.

Brian A. Hargreaves

Papers

Metal-Induced Artifacts in MRI

SEMAC: Slice Encoding for Metal Artifact Correction in MRI

Water-fat separation with IDEAL gradient-echo imaging.

Design and analysis of a practical 3D cones trajectory.

Improved Pediatric MR Imaging with Compressed Sensing