AI RESEARCH
Enhancing Medical Image Segmentation via Heat Conduction Equation
arXiv CS.CV
•
ArXi:2511.03260v2 Announce Type: replace Medical image segmentation models struggle to achieve efficient global context modeling and long-range dependency reasoning under practical computational budgets. In this work, we propose a hybrid architecture utilizing U-Mamba with Heat Conduction Equation, which combines state-space modules for efficient long-range reasoning with Heat Conduction Operators (HCOs) in the bottleneck layers, simulating frequency-domain thermal diffusion for enhanced semantic abstraction.