Fuzzy segmentation and black widow-based optimal SVM for skin disease classification.
The skin, which has seven layers, is the main human organ and external barrier. According to the World Health Organization (WHO), skin cancer is the fourth leading cause of non-fatal disease risk. In medicinal fields, skin disease classification is a major challenging issue due to inaccurate outputs...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 59; no. 10; pp. 2019 - 2036 |
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| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Oct2021
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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=152447248&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 152447248 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Oct2021 vid: 59 iid: 10 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 152447248 151999683 152447248 NLM34417956 10.1007/s11517-021-02415-w NLM34417956 152447248 ppf: 2019 ppct: 17 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Fuzzy segmentation and black widow-based optimal SVM for skin disease classification. aug: au: Raju, D. Naveen Shanmugasundaram, Hariharan Sasikumar, R. affil: Department of Computer Science and Engineering, Sri Sairam Institute of Technology, Chennai, India sug: subj: Skin Neoplasms Skin Diseases Image Processing, Computer Assisted Logic Algorithms Scales ab: The skin, which has seven layers, is the main human organ and external barrier. According to the World Health Organization (WHO), skin cancer is the fourth leading cause of non-fatal disease risk. In medicinal fields, skin disease classification is a major challenging issue due to inaccurate outputs, overfitting, larger computational cost, and so on. We presented a novel approach of support vector machine-based black widow optimization (SVM-BWO) for skin disease classification. Five different kinds of skin disease images are taken such as psoriasis, paederus, herpes, melanoma, and benign with healthy images which are chosen for this work. The pre-processing step is handled to remove the noises from the original input images. Thereafter, the novel fuzzy set segmentation algorithm subsequently segments the skin lesion region. From this, the color, gray-level co-occurrence matrix texture, and shape features are extracted for further process. Skin disease is classified with the usage of the SVM-BWO algorithm. The implementation works are handled in MATLAB-2018a, thereby the dataset images were collected from ISIC-2018 datasets. Experimentally, various kinds of performance analyses with state-of-the-art techniques are performed. Anyway, the proposed methodology outperforms better classification accuracy of 92% than other methods. Workflow diagram of the proposed methodology. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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