Covid-19 related Lung Consolidation’s Digital signature in CT scans

Abstract

Introduction: Research analyzing COVID-19 CT imagery categorizes visual findings into three specific groups, the third of which is lung consolidation (LC).Objective: This study evaluates CT scans from RT-PCR-confirmed COVID-19 cases to define the digital signature of lung consolidation based on grayscale pixel intensity.Methods: By leveraging statistical analysis and modelization techniques, we implemented a dual-threshold filter in Python to achieve efficient CT image segmentation.Results:1- The pixel’s grayscale values of Covid-19 related lung consolidation are normally distributed2- The proposed filter successfully isolates the lung consolidation spotsConclusion: This study presents a novel statistical framework for identifying COVID-19 lung consolidation patterns in CT imagery. Given the observedvariability across different imaging hardware and geographic cohorts, further investigation is required to improve the model's generalizability.