SurgMamba: A Hierarchical Hybrid CNN-Mamba Network with Adaptive Fusion for 2D Surgical Image Semantic Segmentation

Surgical full scene segmentation is essential for laparoscopic assistance but remains challenging due to the high visual similarity among anatomical structures, and illumination variations caused by single moving light source. Moreover, accurately segmenting thin, elongated instruments is still difficult, especially when they appear at oblique orientations. Although Mamba-based segmentation methods effectively model long-range spatial relationships through state-space updates, their 2D selective scan strategy is limited in capturing the oblique spatial distributions of surgical instruments. To address these challenges, a holistic vision Mamba block (HVMamba) is proposed with a Holistic Directional Selective Scan module (HSSD) module to integrate anisotropic spatial features from multiple directions while simultaneously modeling cross-channel dependencies to address ambiguous visual features and complex illumination. Specifically, HSSD comprises an Attention-Guided Holistic Directional Selective Scan (AHSD) for efficient integration of horizontal and oblique spatial features under the guidance of cross-coordinate relationships, and a Channel-aware Directional Selective Scan (CASD) to model bidirectional cross-channel dependencies and enhance responses in ambiguous regions. Based on HVMamba, a hierarchical hybrid network, SurgMamba, is further developed by combining an HVMamba branch with a convolutional neural network branch to jointly capture global and local representations. The two types of representations are adaptively fused by Local-Global Feature Coupling Units (LG-FCUs) in the encoder and an Attention-Aware Gating Mechanism (AGM) in the prediction head. Experiments on two public datasets demonstrate that SurgMamba achieves superior performance over state-of-the-art methods, particularly in challenging cases involving obliquely oriented thin instruments, strong specular highlights, and low-contrast tissue boundaries. Code is available at https://github.com/hailinhhh/SurgMamba.