Department of Pharmacy, Osmania University, Hyderabad, Telangana, India
Mini Review
Application of Deep Learning for Whole-Lung and Lung-Lesion Quantification in Computerized Tomography Despite Inconsistent Ground Truth
Author(s): Devashish Nath*
Computed Tomography (CT) imaging is a crucial tool for diagnosing, characterizing, prognosticating and monitoring disease progression in patients
infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, to evaluate lung abnormalities in a consistent and
reliable manner, accurate segmentation and quantification of both the entire lung and lung lesions (abnormalities) in chest CT images of COVID-19
patients is necessary. Unfortunately, manual segmentation and quantification of a large dataset can be time-consuming and have low inter- and
intra-observer agreement, even for experienced radiologists... Read More»
DOI:
10.37421/2684-494X.2023.8.62
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