A Combined Image Segmentation and Classification Approach for COVID-19 Infected Lungs

Abstract

Lung infection or sickness is one of the most common acute ailments in humans. Pneumonia is one of the most common lung infections, and the annual global mortality rate from untreated pneumonia is increasing. Because of its rapid spread, pneumonia caused by the Coronavirus Disease (COVID-19) has emerged as a global danger as of December 2019. At the clinical level, the COVID-19 is frequently measured using a Computed Tomography Scan Slice (CTS) or a Chest X-ray. The goal of this study is to develop an image processing method for analysing COVID-19 infection in CT Scan patients. The images in this study were preprocessed using the Hybrid Swarm Intelligence and Fuzzy DPSO algorithms. According to extensive computer simulations, the persistent learning strategy for CT image segmentation using image enhancement is more efficient and adaptive than the Medical Image Segmentation (MIS) method. The findings suggest that the proposed method is more dependable, accurate, and simple than existing methods.

A Review Study of the Deep Learning Techniques used for the Classification of Chest Radiological Images for COVID-19 Diagnosis

“…Some other problems in the field of image processing could also be combined with image classification to aid detection. Sangeetha et al ( Sangeetha et al, 2021 ) utilized Hybrid Swarm Intelligence and Fuzzy DPSO to pre-process inputs with the goal of lighting more meaningful information for lung segmentation and quantification at first. Second a new approach called Dropout CNN classification was used to detect abnormalities of lung images, so as to determine whether the patient was infected, which could be used to classify patients.…”

“… Parka et al ( Park et al, 2021 ) Apr-21 Chest X-Ray Valencian Region Medical Image Bank [BIMCV] (De La Iglesia Vay´a et al, 2020), Brixia (Signoroni et al, 2020b) National Institutes of Health [NIH] (Wang et al, 2017) CheXpert He et al ( He et al, 2021 ) May-21 Chest CT COVID-19 CT Lung and Infection Segmentation Dataset, v1.0. (M.Jun, G.Cheng, 2020) MosMedData: Chest CT Scans with COVID-19 Related Findings, 2020 COVID-19 radiology-data collection and preparation for Artificial Intelligence (H. B. Jenssen, 2020) Sangeetha et al ( Sangeetha et al, 2021 ) Aug-21 Chest CT Radiological Society of North America (RSNA) Zhao et al ( Zhao et al, 2021 ) Aug-21 Chest X-Ray The RSNA International COVID-19 Open Radiology Database (RICORD). (Tsai, E.B.…”

Effect of Urbanization Through Land Coverage Classification

“…By offering shade, lowering temperatures, enhancing air quality, and fostering biodiversity, Chennai’s urban green areas reduce the impacts of heat islands and promote sustainable urban planning. There is room for further research in this area, as the spatial features of land cover, including green infrastructure that provides ecosystem services in urban settings, have not been often investigated (Sangeetha, Afreen, & Ahmad, 2021, Sangeetha, Dhaya, et al., 2021). Urban land cover classifications based on multi‐temporal remote sensing provide a platform for assessing these spatial environmental changes and estimating their impact on the provision of ecosystem services (Pullanikkatil et al., 2016).…”

“…The amount and state of ecosystem services are becoming more frequently assessed using data from remote sensing. Based on or in conjunction with remote sensing data, there has recently been an increase in research interest and targeted initiatives to map and/or monitor urban ecosystem services (Sangeetha, Afreen, & Ahmad, 2021, Sangeetha, Dhaya, et al., 2021). Benefit transfer and a modernized valuation methodology enhance the representation of the provision of environmental services for cities, boosting spatial relevance and filling in data gaps, making evaluation more effective and useful for urban planning.…”

Navigating the Future of Healthcare: A Review of Emerging Technology Implementation

“…One of the most commonly occurring acute disorders in people is an infection or illness. Pneumonia is a highly widespread respiratory infection, with a rising annual global mortality rate when left untreated [10]. Pneumonia ranks among the most prevalent respiratory conditions.…”