AI RESEARCH
Resource-Aware Evolutionary Neural Architecture Search for Cardiac MRI Segmentation
arXiv CS.AI
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ArXi:2605.08238v1 Announce Type: cross Cardiac magnetic resonance (CMR) segmentation underpins quantitative assessment of ventricular structure and function, yet reliable delineation remains difficult due to low tissue contrast, fuzzy boundaries, and inter scan variability. We present CardiacNAS, an evolutionary neural architecture search (NAS) framework that couples a UNet like supernet with a cardiac aware search space spanning depth width, kernel size, filter size, attention, fusion, activation, dropout, and residual scaling.