Densely Connected Swin-UNet for Multiscale Information Aggregation in Medical Image Segmentation-Reference-Cited by-同舟云学术

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Densely Connected Swin-UNet for Multiscale Information Aggregation in Medical Image Segmentation

Published:2023-10-08 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Image Processing (ICIP)
language:
Short-container-title:

Author:

Wang Ziyang¹,Su Meiwen²,Zheng Jian-Qing³,Liu Yang⁴

Affiliation:

1. University of Oxford,Department of Computer Science,UK

2. University of Hong Kong,Department of Statistics and Actuarial Science,China

3. University of Oxford,Kennedy Institute of Rheumatology,UK

4. University of Plymouth,Department of Computer Science,UK

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10221937/10221892/10222451.pdf?arnumber=10222451

Reference36 articles.

1. RAR-U-NET: A Residual Encoder to Attention Decoder by Residual Connections Framework for Spine Segmentation Under Noisy Labels

2. Attention u-net: Learning where to look for the pancreas;oktay,2018

3. Squeeze-and-Excitation Networks

4. Recurrent residual convolutional neural network based on u-net (r2u-net) for medical image segmentation;alom,2018

5. Quadruple Augmented Pyramid Network for Multi-class COVID-19 Segmentation via CT

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1. Semi-Mamba-UNet: Pixel-level contrastive and cross-supervised visual Mamba-based UNet for semi-supervised medical image segmentation;Knowledge-Based Systems;2024-09

2. Provably Convergent Learned Inexact Descent Algorithm for Low-Dose CT Reconstruction;Journal of Scientific Computing;2024-08-20

3. Img2Loc: Revisiting Image Geolocalization using Multi-modality Foundation Models and Image-based Retrieval-Augmented Generation;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10

4. MixSegNet: Fusing multiple mixed-supervisory signals with multiple views of networks for mixed-supervised medical image segmentation;Engineering Applications of Artificial Intelligence;2024-07

5. TriConvUNeXt: A Pure CNN-Based Lightweight Symmetrical Network for Biomedical Image Segmentation;Journal of Imaging Informatics in Medicine;2024-04-23

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