MRT-LBMSegNet-Att

MRT-LBMSegNet-Att is a physics-inspired semantic segmentation architecture that combines Multi-Relaxation-Time (MRT) Lattice Boltzmann blocks with attention mechanisms in an encoder–decoder framework. By integrating MRT collision dynamics, lattice-based feature propagation, and multi-scale attention, the network effectively captures both local details and global contextual information. Skip connections preserve fine spatial features, enabling accurate and robust segmentation while maintaining high computational efficiency and interpretability across a wide range of medical and computer vision applications.