AAAI 2026technical0 citations
EccoMamba: Enhanced Cross-hierarchical Continuity Orthogonal Mamba for Medical Image Segmentation
Junlin Xu, Jincan Li, Feifei Cui, Zhuang Zhang, Jialiang Yang, Shuting Jin, Qiangguo Jin, Yajie Meng
Abstract
Medical image segmentation plays a crucial role in clinical diagnosis, lesion quantification, and preoperative planning. However, existing Mamba-based architectures, which rely on fixed-direction sequence modeling and flatten images into one-dimensional (1D) sequences, struggle to capture hierarchical anatomical features and spatial dependencies, thereby limiting their representational capacity for complex medical structures. To address these limitations, we propose EccoMamba (Enhanced Cross-hierarchical Continuity Orthogonal Mamba), a U-shaped encoder--decoder framework designed for medical image segmentation. In the encoder
BibTeX
@inproceedings{aaai2026_eccomambaenhance,
title = {EccoMamba: Enhanced Cross-hierarchical Continuity Orthogonal Mamba for Medical Image Segmentation},
author = {Junlin Xu and Jincan Li and Feifei Cui and Zhuang Zhang and Jialiang Yang and Shuting Jin and Qiangguo Jin and Yajie Meng},
booktitle = {AAAI 2026},
year = {2026}
}