AC-MAMBASEG: An adaptive convolution and Mamba-based architecture for enhanced skin lesion segmentation

arXiv:2405.03011v1 Announce Type: new
Abstract: Skin lesion segmentation is a critical task in computer-aided diagnosis systems for dermatological diseases. Accurate segmentation of skin lesions from medical images is essential for early detection, diagnosis, and treatment planning. In this paper, we propose a new model for skin lesion segmentation namely AC-MambaSeg, an enhanced model that has the hybrid CNN-Mamba backbone, and integrates advanced components such as Convolutional Block Attention Module (CBAM), Attention Gate, and Selective Kernel Bottleneck. AC-MambaSeg leverages the Vision …

architecture arxiv convolution cs.ai cs.cv mamba segmentation type