mlsanityData to 14 Oct 2026

Medical Image Segmentation via Sparse Coding Decoder

arXiv 2310.10957 ↗First posted 17 Oct 2023eess.IV cs.CVcited by 3

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Abstract (arXiv)

Transformers have achieved significant success in medical image segmentation, owing to its capability to capture long-range dependencies. Previous works incorporate convolutional layers into the encoder module of transformers, thereby enhancing their ability to learn local relationships among pixels. However, transformers may suffer from limited generalization capabilities and reduced robustness, attributed to the insufficient spatial recovery ability of their decoders. To address this issue, A convolution sparse vector coding based decoder is proposed , namely CAScaded multi-layer Convolutional Sparse vector Coding DEcoder (CASCSCDE), which represents features extracted by the encoder using sparse vectors. To prove the effectiveness of our CASCSCDE, The widely-used TransUNet model is chosen for the demonstration purpose, and the CASCSCDE is incorporated with TransUNet to establish the TransCASCSCDE architecture. Our experiments demonstrate that TransUNet with CASCSCDE significantly enhances performance on the Synapse benchmark, obtaining up to 3.15% and 1.16% improvements in DICE and mIoU scores, respectively. CASCSCDE opens new ways for constructing decoders based on convolutional sparse vector coding.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 31 of its 49 references that are in the map. First posted on arXiv 17 Oct 2023.

Builds on

31 of 49 references.

References · 31

  1. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  3. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,139
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  5. 2021SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformerscited by 2,940
  6. 2021Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutionscited by 1,962
  7. 2021TransUNet: Transformers Make Strong Encoders for Medical Image Segmentationcited by 1,558
  8. 2018UNet++: A Nested U-Net Architecture for Medical Image Segmentationcited by 1,525
  9. 2018Attention U-Net: Learning Where to Look for the Pancreascited by 1,435
  10. 2021Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentationcited by 1,222
  11. 2021PVT v2: Improved Baselines with Pyramid Vision Transformercited by 751
  12. 2022MaxViT: Multi-Axis Vision Transformercited by 476
19 more
  1. 2020PraNet: Parallel Reverse Attention Network for Polyp Segmentationcited by 460
  2. 2021Conditional Positional Encodings for Vision Transformerscited by 406
  3. 2020UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentationcited by 332
  4. 2021Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformerscited by 159
  5. 2018Reverse Attention for Salient Object Detectioncited by 113
  6. 2021MISSFormer: An Effective Medical Image Segmentation Transformercited by 103
  7. 2021Mixed Transformer U-Net For Medical Image Segmentationcited by 95
  8. 2022HiFormer: Hierarchical Multi-scale Representations Using Transformers for Medical Image Segmentationcited by 95
  9. 2022Stepwise Feature Fusion: Local Guides Globalcited by 56
  10. 2016Convolutional Neural Networks Analyzed via Convolutional Sparse Codingcited by 52
  11. 2022TransDeepLab: Convolution-Free Transformer-based DeepLab v3+ for Medical Image Segmentationcited by 43
  12. 2023Multi-scale Hierarchical Vision Transformer with Cascaded Attention Decoding for Medical Image Segmentationcited by 34
  13. 2022Class-Aware Adversarial Transformers for Medical Image Segmentationcited by 33
  14. 2020DC-UNet: Rethinking the U-Net Architecture with Dual Channel Efficient CNN for Medical Images Segmentationcited by 28
  15. 2022DAE-Former: Dual Attention-guided Efficient Transformer for Medical Image Segmentationcited by 27
  16. 2018On Multi-Layer Basis Pursuit, Efficient Algorithms and Convolutional Neural Networkscited by 21
  17. 2022TFCNs: A CNN-Transformer Hybrid Network for Medical Image Segmentationcited by 18
  18. 2023Enhancing Medical Image Segmentation with TransCeption: A Multi-Scale Feature Fusion Approachcited by 11
  19. 2021CSC-Unet: A Novel Convolutional Sparse Coding Strategy Based Neural Network for Semantic Segmentationcited by 3

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Cited by year

Citing papers per year: 2023: 1; 2024: 1; 2025: 1.

3 papers.

  1. 2025WEEP: A Differentiable Nonconvex Sparse Regularizer via Weakly-Convex Envelopecited by 1
  2. 2023Deep-learning-based decomposition of overlapping-sparse images: application at the vertex of neutrino interactionscited by 0
  3. 2024KANDU-Net:A Dual-Channel U-Net with KAN for Medical Image Segmentationcited by 0