Identifying Severity of COVID-19 Medical Images by Categorizing Using HSDC Model
作者机构:Department of Computing TechnologiesSchool of ComputingSRM Institute of Science and TechnologyChengalpattuTamilnadu603203India
出 版 物:《Computer Systems Science & Engineering》 (计算机系统科学与工程(英文))
年 卷 期:2023年第47卷第10期
页 面:613-635页
学科分类:08[工学] 0812[工学-计算机科学与技术(可授工学、理学学位)]
主 题:CT-scan convolution neural network(CNN) deep CNN(HSDC) hybrid support vector machine(SVM) improved chicken swarmoptimization(ICHO) COVID-19 and image profile(IP)
摘 要:Since COVID-19 infections are increasing all over the world,there is a need for developing solutions for its early and accurate diagnosis is a *** for COVID-19 include screeningmethods like Chest X-rays and Computed Tomography(CT)*** work must be done on preprocessing the datasets,such as eliminating the diaphragm portions,enhancing the image intensity,and minimizing *** addition to the detection of COVID-19,the severity of the infection needs to be *** HSDC model is proposed to solve these problems,which will detect and classify the severity of COVID-19 from X-ray and CT-scan *** CT-scan images,the histogram threshold of the input image is adaptively determined using the ICH Swarm Optimization Segmentation(ICHSeg)*** on the Statistical and Shape-based feature vectors(FVs),the extracted regions are classified using a Hybrid model for CT images(HSDCCT)*** the infections are detected,it’s classified as Normal,Moderate,and Severe.A fused FHI is formed for X-ray images by extracting the features of Histogram-oriented gradient(HOG)and Image profile(IP).The FHI features of X-ray images are classified using Hybrid Support Vector Machine(SVM)and Deep Convolutional Neural Network(DCNN)HSDCX algorithm into COVID-19 or else Pneumonia,or *** results have shown that the accuracy of the HSDC model attains the highest of 94.6 for CT-scan images and 95.6 for X-ray images when compared to SVM and *** study thus significantly helps medical professionals and doctors diagnose COVID-19 infections quickly,which is the most needed in current years.