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Pneumonia is one of the foremost lung diseases and untreated pneumonia willlead to serious threats for all age groups. The proposed work aims to extractand evaluate the Coronavirus disease (COVID-19) caused pneumonia infection inlung using CT scans. We propose an image-assisted system to extract COVID-19infected sections from lung CT scans (coronal view). It includes followingsteps: (i) Threshold filter to extract the lung region by eliminating possibleartifacts; (ii) Image enhancement using Harmony-Search-Optimization and Otsuthresholding; (iii) Image segmentation to extract infected region(s); and (iv)Region-of-interest (ROI) extraction (features) from binary image to computelevel of severity. The features that are extracted from ROI are then employedto identify the pixel ratio between the lung and infection sections to identifyinfection level of severity. The primary objective of the tool is to assist thepulmonologist not only to detect but also to help plan treatment process. As aconsequence, for mass screening processing, it will help prevent diagnosticburden.

Harmony-Search and Otsu based System for Coronavirus Disease (COVID-19) Detection using Lung CT Scan Images