mlsanityData to 7 Oct 2026

LCAUnet: A skin lesion segmentation network with enhanced edge and body fusion

arXiv 2305.00837 ↗First posted 1 May 2023eess.IV cs.CV cs.LGcited by 1

Not on the map. Why?

Abstract (arXiv)

Accurate segmentation of skin lesions in dermatoscopic images is crucial for the early diagnosis of skin cancer and improving the survival rate of patients. However, it is still a challenging task due to the irregularity of lesion areas, the fuzziness of boundaries, and other complex interference factors. In this paper, a novel LCAUnet is proposed to improve the ability of complementary representation with fusion of edge and body features, which are often paid little attentions in traditional methods. First, two separate branches are set for edge and body segmentation with CNNs and Transformer based architecture respectively. Then, LCAF module is utilized to fuse feature maps of edge and body of the same level by local cross-attention operation in encoder stage. Furthermore, PGMF module is embedded for feature integration with prior guided multi-scale adaption. Comprehensive experiments on public available dataset ISIC 2017, ISIC 2018, and PH2 demonstrate that LCAUnet outperforms most state-of-the-art methods. The ablation studies also verify the effectiveness of the proposed fusion techniques.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 33 of its 61 references that are in the map. First posted on arXiv 1 May 2023.

Builds on

33 of 61 references.

References · 33

  1. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  3. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  4. 2016Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localizationcited by 6,690
  5. 2014Fully Convolutional Networks for Semantic Segmentationcited by 4,845
  6. 2021SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformerscited by 2,923
  7. 2016V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentationcited by 2,284
  8. 2021TransUNet: Transformers Make Strong Encoders for Medical Image Segmentationcited by 1,552
  9. 2018UNet++: A Nested U-Net Architecture for Medical Image Segmentationcited by 1,518
  10. 2018Attention U-Net: Learning Where to Look for the Pancreascited by 1,420
  11. 2021Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentationcited by 1,218
  12. 2019Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)cited by 657
21 more
  1. 2015Holistically-Nested Edge Detectioncited by 590
  2. 2017Skin Lesion Analysis Toward Melanoma Detection: A Challenge at the 2017 International Symposium on Biomedical Imaging (ISBI), Hosted by the International Skin Imaging Collaboration (ISIC)cited by 549
  3. 2022TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformerscited by 464
  4. 2018Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature Transformcited by 369
  5. 2017Road Extraction by Deep Residual U-Netcited by 333
  6. 2021TransFuse: Fusing Transformers and CNNs for Medical Image Segmentationcited by 258
  7. 2022DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detectioncited by 224
  8. 2021Pixel Difference Networks for Efficient Edge Detectioncited by 167
  9. 2016Richer Convolutional Features for Edge Detectioncited by 141
  10. 2021DS-TransUNet:Dual Swin Transformer U-Net for Medical Image Segmentationcited by 126
  11. 2020DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentationcited by 125
  12. 2021Multi-Compound Transformer for Accurate Biomedical Image Segmentationcited by 42
  13. 2022Contextual Attention Network: Transformer Meets U-Netcited by 33
  14. 2019A Mutual Bootstrapping Model for Automated Skin Lesion Segmentation and Classificationcited by 32
  15. 2020KiU-Net: Overcomplete Convolutional Architectures for Biomedical Image and Volumetric Segmentationcited by 32
  16. 2019FocusNet: An attention-based Fully Convolutional Network for Medical Image Segmentationcited by 24
  17. 2019DSNet: Automatic Dermoscopic Skin Lesion Segmentationcited by 22
  18. 2018A Multi-stage Framework with Context Information Fusion Structure for Skin Lesion Segmentationcited by 12
  19. 2013Lesion Border Detection in Dermoscopy Images Using Ensembles of Thresholding Methodscited by 8
  20. 2018Select, Attend, and Transfer: Light, Learnable Skip Connectionscited by 6
  21. 2019SLSNet: Skin lesion segmentation using a lightweight generative adversarial networkcited by 4

Built on by

Cited by year

Citing papers per year: 2025: 1.

1 paper.

  1. 2025CENet: Context Enhancement Network for Medical Image Segmentationcited by 5