Cargando…
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...
Autores principales: | Comelli, Albert, Coronnello, Claudia, Dahiya, Navdeep, Benfante, Viviana, Palmucci, Stefano, Basile, Antonio, Vancheri, Carlo, Russo, Giorgio, Yezzi, Anthony, Stefano, Alessandro |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321165/ https://www.ncbi.nlm.nih.gov/pubmed/34460569 http://dx.doi.org/10.3390/jimaging6110125 |
Ejemplares similares
-
Performance of Radiomics Features in the Quantification of Idiopathic Pulmonary Fibrosis from HRCT
por: Stefano, Alessandro, et al.
Publicado: (2020) -
Deep Learning-Based Methods for Prostate Segmentation in Magnetic Resonance Imaging
por: Comelli, Albert, et al.
Publicado: (2021) -
An Overview of In Vitro Assays of (64)Cu-, (68)Ga-, (125)I-, and (99m)Tc-Labelled Radiopharmaceuticals Using Radiometric Counters in the Era of Radiotheranostics
por: Benfante, Viviana, et al.
Publicado: (2023) -
A preliminary PET radiomics study of brain metastases using a fully automatic segmentation method
por: Stefano, Alessandro, et al.
Publicado: (2020) -
Anti-Arthritic and Anti-Cancer Activities of Polyphenols: A Review of the Most Recent In Vitro Assays
por: Ali, Muhammad, et al.
Publicado: (2023)