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International Journal of Computer Assisted Radiology and Surgery

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03-12-2021 | Original Article

Anisotropic neural deblurring for MRI acceleration

Authors: Maya Mayberg, Michael Green, Mark Vasserman, Dominique Raichman, Eugenia Belenky, Michael Wolf, Shai Shrot, Nahum Kiryati, Eli Konen, Arnaldo Mayer

Published in: International Journal of Computer Assisted Radiology and Surgery | Issue 2/2022

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Abstract

Purpose

MRI has become the tool of choice for brain imaging, providing unrivalled contrast between soft tissues, as well as a wealth of information about anatomy, function, and neurochemistry. Image quality, in terms of spatial resolution and noise, is strongly dependent on acquisition duration. A typical brain MRI scan may last several minutes, with total protocol duration often exceeding 30 minutes. Long scan duration leads to poor patient experience, long waiting time for appointments, and high costs. Therefore, shortening MRI scans is crucial. In this paper, we investigate the enhancement of low-resolution (LR) brain MRI scanning, to enable shorter acquisition times without compromising the diagnostic value of the images.

Methods

We propose a novel fully convolutional neural enhancement approach. It is optimized for accelerated LR MRI acquisitions obtained by reducing the acquisition matrix size only along phase encoding direction. The network is trained to transform the LR acquisitions into corresponding high-resolution (HR) counterparts in an end-to-end manner. In contrast to previous neural-based MRI enhancement algorithms, such as DAGAN, the LR images used for training are real acquisitions rather than smoothed, downsampled versions of the HR images.

Results

The proposed method is validated qualitatively and quantitatively for an acceleration factor of 4. Favourable comparison is demonstrated against the state-of-the-art DeblurGAN and DAGAN algorithms in terms of PSNR and SSIM scores. The result was further confirmed by an image quality rating experiment performed by four senior neuroradiologists.

Conclusions

The proposed method may become a valuable tool for scan time reduction in brain MRI. In continuation of this research, the validation should be extended to larger datasets acquired for different imaging protocols, and considering several MRI machines produced by different vendors.

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Title: Anisotropic neural deblurring for MRI acceleration
Authors: Maya Mayberg
Michael Green
Mark Vasserman
Dominique Raichman
Eugenia Belenky
Michael Wolf
Shai Shrot
Nahum Kiryati
Eli Konen
Arnaldo Mayer
Publication date: 03-12-2021
Publisher: Springer International Publishing
Published in: International Journal of Computer Assisted Radiology and Surgery / Issue 2/2022
Print ISSN: 1861-6410
Electronic ISSN: 1861-6429
DOI: https://doi.org/10.1007/s11548-021-02535-6

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Abstract

Purpose

Methods

Results

Conclusions

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