Self-supervised super-resolution of 2-D pre-clinical MRI acquisitions

Lin Guo; Samuel W. Remedios; Alexandru Korotcov; Dzung L. Pham

doi:10.1117/12.3016094

2 April 2024 Self-supervised super-resolution of 2-D pre-clinical MRI acquisitions

Lin Guo, Samuel W. Remedios, Alexandru Korotcov, Dzung L. Pham

Proceedings Volume 12930, Medical Imaging 2024: Clinical and Biomedical Imaging; 129302K (2024) https://doi.org/10.1117/12.3016094
Event: SPIE Medical Imaging, 2024, San Diego, California, United States

Conference Poster

Abstract

Animal models are pivotal in disease research and the advancement of therapeutic methods. The translation of results from these models to clinical applications is enhanced by employing technologies which are consistent for both humans and animals, like Magnetic Resonance Imaging (MRI), offering the advantage of longitudinal disease evaluation without compromising animal welfare. However, current animal MRI techniques predominantly employ 2D acquisitions due to constraints related to organ size, scan duration, image quality, and hardware limitations. While 3D acquisitions are feasible, they are constrained by longer scan times and ethical considerations related to extended sedation periods. This study evaluates the efficacy of SMORE, a self-supervised deep learning super-resolution approach, to enhance the through-plane resolution of anisotropic 2D MRI scans into isotropic resolutions. SMORE accomplishes this by self-training with high-resolution in-plane data, thereby eliminating domain discrepancies between the input data and external training sets. The approach is tested on mouse MRI scans acquired across a range of through-plane resolutions. Experimental results show SMORE substantially outperforms traditional interpolation methods. Additionally, we find that pre-training offers a promising approach to reduce processing time without compromising performance.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Lin Guo, Samuel W. Remedios, Alexandru Korotcov, and Dzung L. Pham "Self-supervised super-resolution of 2-D pre-clinical MRI acquisitions", Proc. SPIE 12930, Medical Imaging 2024: Clinical and Biomedical Imaging, 129302K (2 April 2024); https://doi.org/10.1117/12.3016094

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