AI RESEARCH

Anatomical Token Uncertainty for Transformer-Guided Active MRI Acquisition

arXiv CS.CV

ArXi:2603.21806v1 Announce Type: new Full data acquisition in MRI is inherently slow, which limits clinical throughput and increases patient discomfort. Compressed Sensing MRI (CS-MRI) seeks to accelerate acquisition by reconstructing images from under-sampled k-space data, requiring both an optimal sampling trajectory and a high-fidelity reconstruction model. In this work, we propose a novel active sampling framework that leverages the inherent discrete structure of a pretrained medical image tokenizer and a latent transformer.