AUTOMATIC OPTIMIZED CNN BASED COVID-19 LUNG INFECTION SEGMENTATION FROM CT IMAGE.

Autor: Priya C; Department of Electronics and Communication Engineering College, Ramanathapuram, Tamilnadu, India., Sithi Shameem Fathima SMH; Department of Electronics and Communication Engineering College, Ramanathapuram, Tamilnadu, India., Kirubanandasarathy N; Department of Electronics and Communication Engineering College, Ramanathapuram, Tamilnadu, India., Valanarasid A; Department of Electronics and Communication Engineering College, Ramanathapuram, Tamilnadu, India., Safana Begam MH; Department of Electronics and Communication Engineering College, Ramanathapuram, Tamilnadu, India., Aiswarya N; Department of Electronics and Communication Engineering College, Ramanathapuram, Tamilnadu, India.
Jazyk: angličtina
Zdroj: Materials today. Proceedings [Mater Today Proc] 2021 Feb 05. Date of Electronic Publication: 2021 Feb 05.
DOI: 10.1016/j.matpr.2021.01.820
Abstrakt: In early 2020, the corona virus disease (COVID-19) has become a global epidemic. The WHO announced the disease as a public health emergency of international importance (PHEIC), and the issue was considered a health emergency. Automated computed tomography (CD) detection of lung infections offers a tremendous opportunity to expand the traditional health approach to resolving COVID-19. But many problems with CT. Facing contaminated areas from fragments, which include greater variability in infectious properties and low-intensity comparison between infections and normal tissues. Moreover, by suppressing the project of an in-depth model, a lot of information cannot be collected over some time.
(© 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the Emerging Trends in Materials Science, Technology and Engineering.)
Databáze: MEDLINE
Externí odkaz: