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Proceedings Paper

Enhancing DW images spatial resolution using correlated gradient information
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Paper Abstract

Diffusion-weighted imaging (DWI) is a magnetic resonance imaging technique commonly used to infer tissue microstructure, however, acquisition time requirements affect the effective spatial resolution for DWI high quality. This paper presents a novel super-resolution strategy to reconstruct high-resolution DW images by linearly combining information from different gradient acquisitions. The strategy comprises two main stages, a representation learning and a high-resolution mapping. In the former stage, information from different gradients is grouped by patch-wise statistical similarities. Representative coefficients are then estimated to represent each group. In the latter stage, adapted patch coefficients predict the high-resolution image while a regularization method eliminates possible reconstruction overlapping effects. Several tests evaluate the method ability to pre- dict high resolution information, PSNR and SSIM metrics were applied to quantitatively measure the quality improvement. Results demonstrate that quality reconstruction outperforms state of art methods in about 0.3 dB for PSNR and 1 % for SSIM.

Paper Details

Date Published: 3 January 2020
PDF: 8 pages
Proc. SPIE 11330, 15th International Symposium on Medical Information Processing and Analysis, 113300I (3 January 2020); doi: 10.1117/12.2542552
Show Author Affiliations
Jennifer Salguero, Univ. Nacional de Colombia (Colombia)
Nelson Velasco, Univ. Nacional de Colombia (Colombia)
Univ. Militar Nueva Granada (Colombia)
Eduardo Romero, Univ. Nacional de Colombia (Colombia)

Published in SPIE Proceedings Vol. 11330:
15th International Symposium on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore; Jorge Brieva, Editor(s)

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