Semi-supervised COVID-19 volumetric pulmonary lesion estimation on CT images using probabilistic active contour and CNN segmentation

PURPOSE: A semi-supervised two-step methodology is proposed to obtain a volumetric estimation of COVID-19-related lesions on Computed Tomography (CT) images. METHODS: First, damaged tissue was segmented from CT images using a probabilistic active contours approach. Second, lung parenchyma was extrac...

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Detalles Bibliográficos
Autores principales: Rodriguez-Obregon, Diomar Enrique, Mejia-Rodriguez, Aldo Rodrigo, Cendejas-Zaragoza, Leopoldo, Gutiérrez Mejía, Juan, Arce-Santana, Edgar Román, Charleston-Villalobos, Sonia, Aljama-Corrales, Tomas, Gabutti, Alejandro, Santos-Díaz, Alejandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10030333/
https://www.ncbi.nlm.nih.gov/pubmed/36993838
http://dx.doi.org/10.1016/j.bspc.2023.104905

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10030333/
https://www.ncbi.nlm.nih.gov/pubmed/36993838
http://dx.doi.org/10.1016/j.bspc.2023.104905

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