Chenhui Wang

The work proposes UniField, a unified multi-modality, multi-task MRI field-strength enhancement framework that consolidates T1, T2, and FLAIR modalities and cross-field tasks such as 64mT-to-3T and 3T-to-7T into a single model, embeds 3D structural priors by operating in the latent space of the pretrained video super-resolution model FlashVSR with LoRA fine-tuning, and introduces a Field-Aware Spectral Rectification Mechanism (FASRM) that adjusts low-, mid-, and high-frequency loss weights according to the physical properties of the source and target fields; it also organizes and publicly releases a paired multi-field MRI dataset from five institutions that is an order of magnitude larger than existing benchmarks, reporting average improvements of about 1.81 dB in PSNR and 9.

The work proposes UniField, a unified multi-modality, multi-task MRI field-strength enhancement framework that consolidates T1, T2, and FLAIR modalities and cross-field tasks such as 64mT-to-3T and 3T-to-7T into a single model, embeds 3D structural priors by operating in the latent space of the pretrained video super-resolution model FlashVSR with LoRA fine-tuning, and introduces a Field-Aware Spectral Rectification Mechanism (FASRM) that adjusts low-, mid-, and high-frequency loss weights according to the physical properties of the source and target fields; it also organizes and publicly releases a paired multi-field MRI dataset from five institutions that is an order of magnitude larger than existing benchmarks, reporting average improvements of about 1.81 dB in PSNR and 9.