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SHFormer: Dynamic Spectral Filtering Convolutional Neural Network and High-pass Kernel Generation Transformer for Adaptive MRI Reconstruction

arXiv cs.CV Medical/Healthcare AI Sriprabha Ramanarayanan, Rahul G. S., Mohammad Al Fahim, Keerthi Ram, Ramesh Venkatesan, Mohanasankar Sivaprakasam 2026-07-22

TL;DR - SHFormer combines dynamic spectral-filtering CNNs with a high-pass kernel generation transformer to preserve fine details in accelerated MRI reconstruction. It improves reconstruction and generalization across heterogeneous, previously unseen MRI domains.

Targets attention models’ tendency to favor low-frequency information and produce overly smooth reconstructions.
Learns mode-specific transferable features while emphasizing context-aware high-frequency details.
Evaluated across supervised, self-supervised, diffusion-based, closed-set, and open-set settings.
Reports best unseen-domain gains of approximately 1 dB PSNR and 0.01 SSIM.

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