FWLICM-Deep Learning: Fuzzy Weighted Local Information C-Means Clustering-Based Lung Lobe Segmentation with Deep Learning for COVID-19 Detection.
Coronavirus (COVID-19) creates an extensive range of respiratory contagions, and it is a kind of ribonucleic acid (RNA) virus, which affects both animals and humans. Moreover, COVID-19 is a new disease, which produces contamination in upper respiration alterritory and lungs. The new COVID is a rapid...
| Publicado en: | Journal of Digital Imaging Vol. 35; no. 6; pp. 1463 - 1479 |
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| Autores principales: | , , , |
| Formato: | diagnostic images equations & formulas tables/charts Journal Article |
| Publicado: |
Springer Nature
Dec2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=160503245&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 160503245 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Dec2022 vid: 35 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 160503245 157814907 160503245 160503245 10.1007/s10278-022-00667-y 160503245 ppf: 1463 ppct: 16 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: FWLICM-Deep Learning: Fuzzy Weighted Local Information C-Means Clustering-Based Lung Lobe Segmentation with Deep Learning for COVID-19 Detection. aug: au: Rajeswari, R. Gampala, Veerraju Maram, Balajee Cristin, R. affil: Department of Electronics and Communication Engineering, Rajalakshmi Institute of Technology, Chennai, India sug: subj: COVID-19 Mortality Lung RNA COVID-19 Testing Methods Respiratory Tract Infections Radiography, Thoracic Cluster Analysis Deep Learning ab: Coronavirus (COVID-19) creates an extensive range of respiratory contagions, and it is a kind of ribonucleic acid (RNA) virus, which affects both animals and humans. Moreover, COVID-19 is a new disease, which produces contamination in upper respiration alterritory and lungs. The new COVID is a rapidly spreading pathogen globally, and it threatens billions of humans' lives. However, it is significant to identify positive cases in order to avoid the spread of plague and to speedily treat infected patients. Hence, in this paper, the WSCA-based RMDL approach is devised for COVID-19 prediction by means of chest X-ray images. Moreover, Fuzzy Weighted Local Information C-Means (FWLICM) approach is devised in order to segment lung lobes. The developed FWLICM method is designed by modifying the Fuzzy Local Information C-Means (FLICM) technique. Additionally, random multimodel deep learning (RMDL) classifier is utilized for the COVID-19 prediction process. The new optimization approach, named water sine cosine algorithm (WSCA), is devised in order to obtain an effective prediction. The developed WSCA is newly designed by incorporating sine cosine algorithm (SCA) and water cycle algorithm (WCA). The developed WSCA-driven RMDL approach outperforms other COVID-19 prediction techniques with regard to accuracy, specificity, sensitivity, and dice score of 92.41%, 93.55%, 92.14%, and 90.02%. pubtype: Academic Journal doctype: diagnostic images equations & formulas tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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