HistDeblur: A Pyramid Trustworthy Framework for Blurry Histologic Artifacts Quality Control-Reference-Cited by-同舟云学术

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HistDeblur: A Pyramid Trustworthy Framework for Blurry Histologic Artifacts Quality Control

Published:2023-12-05 Issue: Volume: Page:2255-2258
ISSN:
Container-title:2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
language:
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Author:

Sun Yuxiang¹,Liu Kai¹,Shen Yiqing²,Han Xiaodan³,Ke Jing¹

Affiliation:

1. Shanghai Jiao Tong University,School of Electronic Information and Electrical Engineering,Shanghai,China

2. Johns Hopkins University,Department of Computer Science,Baltimore,USA

3. Fudan University,Zhongshan Hospital,Department of Anaesthesiology,Shanghai,China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shanghai

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10385250/10385251/10385259.pdf?arnumber=10385259

Reference16 articles.

1. 100,000 histological images of human colorectal cancer and healthy tissue;Kather,2018

2. A deep journey into image enhancement: A survey of current and emerging trends

3. DeepFocus: Detection of out-of-focus regions in whole slide digital images using deep learning

4. Autofocus methods of whole slide imaging systems and the introduction of a second-generation independent dual sensor scanning method

5. An Automated Blur Detection Method for Histological Whole Slide Imaging

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