Lung Segmentation on High-Resolution Computerized Tomography Images Using Deep Learning: A Preliminary Step for Radiomics Studies

Background: The aim of this work is to identify an automatic, accurate, and fast deep learning segmentation approach, applied to the parenchyma, using a very small dataset of high-resolution computed tomography images of patients with idiopathic pulmonary fibrosis. In this way, we aim to enhance the...

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Detalhes bibliográficos

Principais autores:	Albert Comelli, Claudia Coronnello, Navdeep Dahiya, Viviana Benfante, Stefano Palmucci, Antonio Basile, Carlo Vancheri, Giorgio Russo, Anthony Yezzi, Alessandro Stefano
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2020-11-01
coleção:	Journal of Imaging
Assuntos:	idiopathic pulmonary fibrosis deep learning lung segmentation high resolution computed tomography radiomics U-Net
Acesso em linha:	https://www.mdpi.com/2313-433X/6/11/125
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