Multicentric thrombus segmentation using an attention-based recurrent network with gradual modality dropout

ArXi:2604.00817v1 Announce Type: new Detecting and delineating tiny targets in 3D brain scans is a central yet under-addressed challenge in medical imaging. In ischemic stroke, for instance, the culprit thrombus is small, low-contrast, and variably expressed across modalities(e.g., susceptibility-weighted T2 blooming, diffusion restriction on DWI/ADC), while real-world multi-center data