U-HRMLP: Refining Segmentation Boundaries in Histopathology Images-Reference-Cited by-同舟云学术

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U-HRMLP: Refining Segmentation Boundaries in Histopathology Images

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

Wang Tao¹,Zhang Kai²,Wang Weijie³,Ma Mingrui⁴,Zhang Ye⁵,Zhao He¹,Liu Guixia¹

Affiliation:

1. Jilin University,College of Computer Science and Technology,China

2. Shandong Normal University,School of Information Science and Engineering,China

3. University of Trento,Department of Information Engineering and Computer Science,Italy

4. Kunming University of Science and Technology,Faculty of Information Engineering and Automation,China

5. Northeast Normal University,School of Information Science and Technology,China

Funder

Nature

Technology Development

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10635099/10635102/10635255.pdf?arnumber=10635255

Reference14 articles.

1. A survey on artificial intelligence in histopathology image analysis

2. Fully convolutional networks for semantic segmentation

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

4. A Deep Attentive Convolutional Neural Network for Automatic Cortical Plate Segmentation in Fetal MRI

5. Medical Transformer: Gated Axial-Attention for Medical Image Segmentation

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