mlsanityData to 7 Oct 2026

MCANet: Medical Image Segmentation with Multi-Scale Cross-Axis Attention

arXiv 2312.08866 ↗First posted 14 Dec 2023eess.IV cs.CVcited by 5

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Abstract (arXiv)

Efficiently capturing multi-scale information and building long-range dependencies among pixels are essential for medical image segmentation because of the various sizes and shapes of the lesion regions or organs. In this paper, we present Multi-scale Cross-axis Attention (MCA) to solve the above challenging issues based on the efficient axial attention. Instead of simply connecting axial attention along the horizontal and vertical directions sequentially, we propose to calculate dual cross attentions between two parallel axial attentions to capture global information better. To process the significant variations of lesion regions or organs in individual sizes and shapes, we also use multiple convolutions of strip-shape kernels with different kernel sizes in each axial attention path to improve the efficiency of the proposed MCA in encoding spatial information. We build the proposed MCA upon the MSCAN backbone, yielding our network, termed MCANet. Our MCANet with only 4M+ parameters performs even better than most previous works with heavy backbones (e.g., Swin Transformer) on four challenging tasks, including skin lesion segmentation, nuclei segmentation, abdominal multi-organ segmentation, and polyp segmentation. Code is available at https://github.com/haoshao-nku/medical_seg.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 60 of its 79 references that are in the map. First posted on arXiv 14 Dec 2023.

Builds on

60 of 79 references.

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38 more
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Cited by year

Citing papers per year: 2024: 1; 2025: 4.

5 papers.

  1. 2024Frontiers in Intelligent Colonoscopycited by 13
  2. 2025Multi-Granularity Vision Fastformer with Fusion Mechanism for Skin Lesion Segmentationcited by 0
  3. 2025Machine Learning-Based Ultrasonic Weld Characterization Using Hierarchical Wave Modeling and Diffusion-Driven Distribution Alignmentcited by 0
  4. 2025Intelligent Communication Mixture-of-Experts Boosted-Medical Image Segmentation Foundation Modelcited by 0
  5. 2025WaveSeg: Enhancing Segmentation Precision via High-Frequency Prior and Mamba-Driven Spectrum Decompositioncited by 0