Pneumothorax segmentation of chest X-rays using improved UNet++-Reference-Cited by-同舟云学术

Pneumothorax segmentation of chest X-rays using improved UNet++

Published:2022-08 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE)
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Author:

Zhang Xing¹,Liu Zhiqin²,Wang Qingfeng²,Chen Bo²

Affiliation:

1. Southwest University of Science and Technology,Department of electronic information,Mianyang,China

2. Southwest University of Science and Technology,School of Computer Science and Technology,Mianyang,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9942815/9943052/09943207.pdf?arnumber=9943207

Reference16 articles.

1. ChestX-Ray8: Hospital-Scale Chest X-Ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases

2. Weakly Supervised Segmentation Framework with Uncertainty: A Study on Pneumothorax Segmentation in Chest X-ray

3. Fully Convolutional Multi-Scale ScSE-DenseNet for Automatic Pneumothorax Segmentation in Chest Radiographs;luo;2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM),2020

4. DeepSDM: Boundary-aware pneumothorax segmentation in chest X-ray images

5. UNet++: A Nested U-Net Architecture for Medical Image Segmentation

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