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TopoMamba improves medical image segmentation with topology-aware scanning

By PulseAugur Editorial · [3 sources] ·

Researchers have developed TopoMamba, a novel framework designed to improve the segmentation of heterogeneous medical visual media. This approach addresses limitations in existing visual state-space models by incorporating topology-aware scanning and a lightweight fusion mechanism. Experiments on various medical datasets demonstrate TopoMamba's superior performance, particularly for segmenting complex structures like curved or thin anatomical features. AI

IMPACT Enhances medical image segmentation accuracy, especially for complex anatomical structures, potentially improving diagnostic capabilities.

RANK_REASON Academic paper detailing a new method for medical image segmentation.

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

TopoMamba improves medical image segmentation with topology-aware scanning

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COVERAGE [3]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    TopoMamba: Topology-Aware Scanning and Fusion for Segmenting Heterogeneous Medical Visual Media

    Visual state-space models (SSMs) have shown strong potential for medical image segmentation, yet their effectiveness is often limited by two practical issues: axis-biased scan ordering weakens the modeling of oblique and curved structures, and naive multi-branch fusion tends to a…

  2. arXiv cs.CV TIER_1 English(EN) · Fuchen Zheng, Chengpei Xu, Long Ma, Weixuan Li, Junhua Zhou, Xuhang Chen, Weihuang Liu, Haolun Li, Quanjun Li, Zhenxi Zhang, Lei Zhao, Chi-Man Pun, Shoujun Zhou ·

    TopoMamba: Topology-Aware Scanning and Fusion for Segmenting Heterogeneous Medical Visual Media

    arXiv:2604.25545v1 Announce Type: new Abstract: Visual state-space models (SSMs) have shown strong potential for medical image segmentation, yet their effectiveness is often limited by two practical issues: axis-biased scan ordering weakens the modeling of oblique and curved stru…

  3. arXiv cs.CV TIER_1 English(EN) · Shoujun Zhou ·

    TopoMamba: Topology-Aware Scanning and Fusion for Segmenting Heterogeneous Medical Visual Media

    Visual state-space models (SSMs) have shown strong potential for medical image segmentation, yet their effectiveness is often limited by two practical issues: axis-biased scan ordering weakens the modeling of oblique and curved structures, and naive multi-branch fusion tends to a…

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