A Pipeline for the Diagnosis and Classification of Lung Lesions for Patients with COVID-19-Reference-Cited by-同舟云学术

A Pipeline for the Diagnosis and Classification of Lung Lesions for Patients with COVID-19

Published:2022-11-10 Issue: Volume: Page:
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Container-title:2022 IEEE 17th International Conference on Computer Sciences and Information Technologies (CSIT)
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Author:

Davydko Oleksandr¹,Horodetska Olena¹,Nastenko Ievgen²,Hladkyi Yaroslav¹,Pavlov Vladimir³,Longo Luca⁴,Linnik Mykola⁵,Galkin Oleksandr¹

Affiliation:

1. National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”,Department of biomedical cybernetics,Kyiv,Ukraine

2. National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”,Amosov National Institute of Cardiovascular Surgery,Department of biomedical cybernetics,Kyiv,Ukraine

3. National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”,Department of biomedical cybernetics

4. Technological University Dublin,AICL Lab School of Computer Science,Dublin,Ireland

5. F.G. Yanovsky National Institute of Phthisiology and Pulmonology of the NAMS of Ukraine,Department of Epidemiology and Organizational Problems of Phthisiology,Kyiv,Ukraine

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10000061/10000064/10000435.pdf?arnumber=10000435

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5. Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem