Feb. 14, 2024, 5:46 a.m. | Kwanseok Oh Jieun Lee Da-Woon Heo Dinggang Shen Heung-Il Suk

cs.CV updates on arXiv.org arxiv.org

Ultrahigh-field (UHF) magnetic resonance imaging (MRI), i.e., 7T MRI, provides superior anatomical details of internal brain structures owing to its enhanced signal-to-noise ratio and susceptibility-induced contrast. However, the widespread use of 7T MRI is limited by its high cost and lower accessibility compared to low-field (LF) MRI. This study proposes a deep-learning framework that systematically fuses the input LF magnetic resonance feature representations with the inferred 7T-like feature representations for brain image segmentation tasks in a 7T-absent environment. Specifically, our …

accessibility brain contrast cost cs.ai cs.cv imaging intensity low mri noise segmentation signal

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