Glfnet: Global-Local (Frequency) Filter Networks for Efficient Medical Image Segmentation-Reference-Cited by-同舟云学术

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Glfnet: Global-Local (Frequency) Filter Networks for Efficient Medical Image Segmentation

Published:2024-05-27 Issue: Volume:34 Page:1-5
ISSN:
Container-title:2024 IEEE International Symposium on Biomedical Imaging (ISBI)
language:
Short-container-title:

Author:

Tragakis Athanasios¹,Liu Qianying²,Kaul Chaitanya²,Roy Swalpa Kumar³,Dai Hang²,Deligianni Fani²,Murray-Smith Roderick²,Faccio Daniele¹

Affiliation:

1. University of Glasgow,School of Physics and Astronomy,Glasgow,UK,G12 8QQ

2. University of Glasgow,School of Computing Science,United Kingdom,G12 8RZ

3. Alipurduar Government Engineering and Management College,Department of Computer Science and Engineering,West Bengal,India,736206

Funder

China Scholarship Council

Google

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10635099/10635102/10635344.pdf?arnumber=10635344

Reference19 articles.

1. U-Net: Convolutional Networks for Biomedical Image Segmentation

2. UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation

3. Focusnet++: Attentive Aggregated Transformations For Efficient And Accurate Medical Image Segmentation

4. An image is worth 16 × 16 words: Transformers for image recognition at scale;Dosovitskiy,2020

5. Swin-Unet: Unet-Like Pure Transformer for Medical Image Segmentation

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