Comparing Different Data Partitioning Strategies for Segmenting Areas Affected by COVID-19 in CT Scans
The main conclusions were as follows: COVID-19 segmentation was slightly better for the slice strategy than for the CT-scan strategy; a comparison of the performance of the automatic COVID-19 segmentation and the interobserver agreement, in a group of 7 CT scans, revealed that there was no statistically significant difference between any metric.
Authors
- Cícero Ferreira Fernandes Costa Filho (ORCID: https://orcid.org/0000-0003-3325-5715)
- Joana Cósta (ORCID: https://orcid.org/0000-0002-4053-5718)
- M. G. F. Costa (ORCID: https://orcid.org/0000-0002-6839-1402)
- Anne de Souza Oliveira (ORCID: https://orcid.org/0000-0002-3123-303X)
Institutions
- Instituto do Câncer do Estado de São Paulo (BR)
- Universidade Federal do Amazonas (BR)
Publication Details
- Journal
- Diagnostics
- Published
- 2024-12-12
- DOI
- https://doi.org/10.3390/diagnostics14242791
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Universidade Federal do Amazonas
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
- Fundação de Amparo à Pesquisa do Estado do Amazonas
- Samsung