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arXiv Computer Vision By Talha Meraj, Tom Flannery, Charlie Cummins, Matt Townend, Thomas C Booth, Peter Crossley, Michael McCann, Ian Overton, Saritha Unnikrishnan

AA-ViT: Anatomically Aware Vision Transformer with Structural and Frequency Guidance for Contrast Enhanced Brain MRI Synthesis

Read the original on arXiv Computer Vision →

The paper introduces AA‑ViT, an anatomically aware vision transformer that synthesizes contrast‑enhanced brain MRI from pre‑contrast modalities (T1, T2, FLAIR) by incorporating structural and frequency guidance. Experiments on the BraTS 2021 dataset show that AA‑ViT preserves anatomical and lesion boundaries, achieving higher PSNR and SSIM than existing methods. A clinical evaluation by four experts on 19 glioma cases yielded a mean score of 3.94/5, indicating promising clinical relevance.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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