mlsanityData to 14 Oct 2026

Patch Network for medical image Segmentation

arXiv 2302.11802 ↗First posted 23 Feb 2023cs.CVcited by 0

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Abstract (arXiv)

Accurate and fast segmentation of medical images is clinically essential, yet current research methods include convolutional neural networks with fast inference speed but difficulty in learning image contextual features, and transformer with good performance but high hardware requirements. In this paper, we present a Patch Network (PNet) that incorporates the Swin Transformer notion into a convolutional neural network, allowing it to gather richer contextual information while achieving the balance of speed and accuracy. We test our PNet on Polyp(CVC-ClinicDB and ETIS- LaribPolypDB), Skin(ISIC-2018 Skin lesion segmentation challenge dataset) segmentation datasets. Our PNet achieves SOTA performance in both speed and accuracy.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 15 of its 18 references that are in the map. First posted on arXiv 23 Feb 2023.

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15 of 18 references.

References · 15

  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
  4. 2020End-to-End Object Detection with Transformerscited by 7,414
  5. 2018Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentationcited by 3,223
  6. 2016Pyramid Scene Parsing Networkcited by 2,479
  7. 2015SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentationcited by 1,487
  8. 2018Attention U-Net: Learning Where to Look for the Pancreascited by 1,435
  9. 2020Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformerscited by 1,369
  10. 2018BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentationcited by 645
  11. 2019UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentationcited by 586
  12. 2016ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentationcited by 291
3 more
  1. 2022Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNscited by 155
  2. 2020DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentationcited by 125
  3. 2018CGNet: A Light-weight Context Guided Network for Semantic Segmentationcited by 94

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