mlsanityData to 14 Oct 2026

GaMNet: A Hybrid Network with Gabor Fusion and NMamba for Efficient 3D Glioma Segmentation

arXiv 2505.05520 ↗First posted 8 May 2025cs.CV cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

Gliomas are aggressive brain tumors that pose serious health risks. Deep learning aids in lesion segmentation, but CNN and Transformer-based models often lack context modeling or demand heavy computation, limiting real-time use on mobile medical devices. We propose GaMNet, integrating the NMamba module for global modeling and a multi-scale CNN for efficient local feature extraction. To improve interpretability and mimic the human visual system, we apply Gabor filters at multiple scales. Our method achieves high segmentation accuracy with fewer parameters and faster computation. Extensive experiments show GaMNet outperforms existing methods, notably reducing false positives and negatives, which enhances the reliability of clinical diagnosis.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 20 of its 32 references that are in the map. First posted on arXiv 8 May 2025.

Builds on

20 of 32 references.

References · 20

  1. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  2. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,139
  3. 2023Mamba: Linear-Time Sequence Modeling with Selective State Spacescited by 4,718
  4. 2016V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentationcited by 2,292
  5. 20163D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotationcited by 1,476
  6. 2018Attention U-Net: Learning Where to Look for the Pancreascited by 1,435
  7. 2024VMamba: Visual State Space Modelcited by 969
  8. 2021UNETR: Transformers for 3D Medical Image Segmentationcited by 959
  9. 2021Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysiscited by 422
  10. 2021nnFormer: Interleaved Transformer for Volumetric Segmentationcited by 180
  11. 2023MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentationcited by 162
  12. 2016The Importance of Skip Connections in Biomedical Image Segmentationcited by 126
8 more
  1. 2022UNETR++: Delving into Efficient and Accurate 3D Medical Image Segmentationcited by 112
  2. 2024SegFormer3D: an Efficient Transformer for 3D Medical Image Segmentationcited by 31
  3. 2025MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Predictioncited by 16
  4. 2024CSCE: Boosting LLM Reasoning by Simultaneous Enhancing of Causal Significance and Consistencycited by 7
  5. 2024Synergistic Spotting and Recognition of Micro-Expression via Temporal State Transitioncited by 6
  6. 2025Efficient Knowledge Transfer in Multi-Task Learning through Task-Adaptive Low-Rank Representationcited by 4
  7. 2025Graph-Driven Multimodal Feature Learning Framework for Apparent Personality Assessmentcited by 2
  8. 2025GAME: Learning Multimodal Interactions via Graph Structures for Personality Trait Estimationcited by 1

Built on by

Not cited yet.