Department of Pharmacy, Osmania University, Hyderabad, Telangana, India
Mini Review
Utilizing Deep Learning for Comprehensive Lung and Lesion Quantification in Computerized Tomography Amidst Inconsistent Ground Truth
Author(s): Devashish Nath*
Computed Tomography (CT) imaging plays a pivotal role in diagnosing, characterizing, predicting outcomes, and tracking disease progression
in individuals affected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Yet, for a consistent and dependable assessment of
pulmonary irregularities, precise segmentation and quantification of both the complete lung and lung lesions (anomalies) in chest CT scans of
COVID-19 patients are indispensable. Regrettably, the manual segmentation and quantification of extensive datasets can prove time-intensive and
yield low levels of agreement both between different observers and within the same observer, even among experienced radiologists... Read More»
DOI:
10.37421/2684-494X.2023.8.92
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