论文标题
使用肺CT扫描图像的冠状病毒疾病（COVID-19）检测的基于Harmony-Search和OTSU的系统
Harmony-Search and Otsu based System for Coronavirus Disease (COVID-19) Detection using Lung CT Scan Images
论文作者
论文摘要
肺炎是最重要的肺部疾病之一，未经治疗的肺炎将对所有年龄段的人群造成严重威胁。拟议的工作旨在提取和评估冠状病毒疾病（Covid-19）引起使用CT扫描在肺中引起肺炎感染。我们提出了一个图像辅助系统，以从肺CT扫描（冠状视图）中提取共vid-19感染切片。它包括以下步骤：（i）通过消除可能的伪影来提取肺部区域的阈值滤波器； （ii）使用Harmony-Search优化和OTSU阈值的图像增强； （iii）图像分割以提取感染区域； （iv）利益区域（ROI）提取（特征）从二进制图像到计算严重程度的水平。然后使用从ROI中提取的特征来识别肺部和感染切片之间的像素比以识别严重程度的感染水平。该工具的主要目的是协助肺科医生不仅检测，而且还可以帮助计划治疗过程。结果，对于大规模筛查处理，它将有助于防止诊断负担。
Pneumonia is one of the foremost lung diseases and untreated pneumonia will lead to serious threats for all age groups. The proposed work aims to extract and evaluate the Coronavirus disease (COVID-19) caused pneumonia infection in lung using CT scans. We propose an image-assisted system to extract COVID-19 infected sections from lung CT scans (coronal view). It includes following steps: (i) Threshold filter to extract the lung region by eliminating possible artifacts; (ii) Image enhancement using Harmony-Search-Optimization and Otsu thresholding; (iii) Image segmentation to extract infected region(s); and (iv) Region-of-interest (ROI) extraction (features) from binary image to compute level of severity. The features that are extracted from ROI are then employed to identify the pixel ratio between the lung and infection sections to identify infection level of severity. The primary objective of the tool is to assist the pulmonologist not only to detect but also to help plan treatment process. As a consequence, for mass screening processing, it will help prevent diagnostic burden.
