Automatic Segmentation of Psoriasis Skin Images Using Adaptive Chimp Optimization Algorithm–Based CNN.
Psoriasis is a severe skin disease that is surveyed outwardly by dermatologists. In recent years, computer vision is the major solution for diagnosing the psoriasis skin disease by segmenting the infected skin images. Besides, many researchers had presented efficient machine learning techniques for...
| Publicado en: | Journal of Digital Imaging Vol. 36; no. 3; pp. 1123 - 1137 |
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| Autores principales: | , |
| Formato: | algorithm pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Jun2023
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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=164473093&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 164473093 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Jun2023 vid: 36 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 164473093 161155368 164473093 164473093 10.1007/s10278-022-00765-x 164473093 ppf: 1123 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Automatic Segmentation of Psoriasis Skin Images Using Adaptive Chimp Optimization Algorithm–Based CNN. aug: au: Mohan, S. Kasthuri, N. affil: Department of ECE, AVS Engineering College, Salem, Tamil Nadu, India sug: subj: Psoriasis Diagnosis Digital Imaging Algorithms Neural Networks (Computer) Image Processing, Computer Assisted Human Animal Studies Primates Sensitivity and Specificity Validity Prediction Models Descriptive Statistics Hunting Behavior, Animal ab: Psoriasis is a severe skin disease that is surveyed outwardly by dermatologists. In recent years, computer vision is the major solution for diagnosing the psoriasis skin disease by segmenting the infected skin images. Besides, many researchers had presented efficient machine learning techniques for segmenting the psoriasis skin images. Nevertheless, accuracy and time consumption of the model are further to be improved. Thus, in this work, we present adaptive chimp optimization algorithm (AChOA)–based convolutional neural network (CNN) which is introduced for automatic segmentation of psoriasis skin images. After pre-processing, the input images are segmented using AChOA-CNN model where weight and bias values of CNN are optimized with the AChOA. The search ability of ChOA is enhanced by adapting the chaotic sequence based on tent map. At final, from the segmented output images, artifacts are removed by applying the threshold module. From the simulation, we attain 97% of accuracy. pubtype: Academic Journal doctype: algorithm pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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