COVID-19 Chest Computed Tomography to Stratify Severity and Disease Extension by Artificial Neural Network Computer-Aided Diagnosis

Purpose: This work aims to develop a computer-aided diagnosis (CAD) to quantify the extent of pulmonary involvement (PI) in COVID-19 as well as the radiological patterns referred to as lung opacities in chest computer tomography (CT). Methods: One hundred thirty subjects with COVID-19 pneumonia who...

詳細記述

保存先:
書誌詳細
出版年:Front Med (Lausanne)
主要な著者: Carvalho, Alysson Roncally S., Guimarães, Alan, Werberich, Gabriel Madeira, de Castro, Stephane Nery, Pinto, Joana Sofia F., Schmitt, Willian Rebouças, França, Manuela, Bozza, Fernando Augusto, Guimarães, Bruno Leonardo da Silva, Zin, Walter Araujo, Rodrigues, Rosana Souza
フォーマット: Artigo
言語:Inglês
出版事項: Frontiers Media S.A. 2020
主題:
Medicine
オンライン･アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC7746855/
https://ncbi.nlm.nih.gov/pubmed/33344471
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fmed.2020.577609
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