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Enhancing COVID-19 CT Image Segmentation: A Comparative Study of Attention and Recurrence in UNet Models.

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Bibliographic Details
Title: Enhancing COVID-19 CT Image Segmentation: A Comparative Study of Attention and Recurrence in UNet Models.
Authors: Buongiorno R; Institute of Information Science and Technologies, National Research Council of Italy (ISTI-CNR), 56124 Pisa, PI, Italy., Del Corso G; Institute of Information Science and Technologies, National Research Council of Italy (ISTI-CNR), 56124 Pisa, PI, Italy., Germanese D; Institute of Information Science and Technologies, National Research Council of Italy (ISTI-CNR), 56124 Pisa, PI, Italy., Colligiani L; Department of Translational Research, Academic Radiology, University of Pisa, 56124 Pisa, PI, Italy., Python L; 2nd Radiology Unit, Pisa University Hospital, 56124 Pisa, PI, Italy., Romei C; 2nd Radiology Unit, Pisa University Hospital, 56124 Pisa, PI, Italy., Colantonio S; Institute of Information Science and Technologies, National Research Council of Italy (ISTI-CNR), 56124 Pisa, PI, Italy.
Source: Journal of imaging [J Imaging] 2023 Dec 18; Vol. 9 (12). Date of Electronic Publication: 2023 Dec 18.
Publication Type: Journal Article
Journal Info: Publisher: MDPI Country of Publication: Switzerland NLM ID: 101698819 Publication Model: Electronic Cited Medium: Internet ISSN: 2313-433X (Electronic) Linking ISSN: 2313433X NLM ISO Abbreviation: J Imaging Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2313-433X
DOI:10.3390/jimaging9120283