Categorization of Common Pigmented Skin Lesions (CPSL) using Multi-Deep Features and Support Vector Machine.
The skin is the main organ. It is approximately 8 pounds for the average adult. Our skin is a truly wonderful organ. It isolates us and shields our bodies from hazards. However, the skin is also vulnerable to damage and distracted from its original appearance: brown, black, or blue, or combinations...
| Published in: | Journal of Digital Imaging Vol. 35; no. 5; pp. 1207 - 1217 |
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| Main Authors: | , , |
| Format: | pictorial research tables/charts Journal Article |
| Published: |
Springer Nature
Oct2022
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=159758931&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 159758931 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Oct2022 vid: 35 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 159758931 156699967 159758931 159758931 10.1007/s10278-022-00632-9 159758931 ppf: 1207 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Categorization of Common Pigmented Skin Lesions (CPSL) using Multi-Deep Features and Support Vector Machine. aug: au: Sethy, Prabira Kumar Behera, Santi Kumari Kannan, Nithiyanathan affil: Department of Electronics, Sambalpur University, Sambalpur, Odisha, India sug: subj: Skin Neoplasms Support Vector Machine Neural Networks (Computer) Factor Analysis Algorithms Descriptive Statistics Human Skin Pigmentation ab: The skin is the main organ. It is approximately 8 pounds for the average adult. Our skin is a truly wonderful organ. It isolates us and shields our bodies from hazards. However, the skin is also vulnerable to damage and distracted from its original appearance: brown, black, or blue, or combinations of those colors, known as pigmented skin lesions. These common pigmented skin lesions (CPSL) are the leading factor of skin cancer, or can say these are the primary causes of skin cancer. In the healthcare sector, the categorization of CPSL is the main problem because of inaccurate outputs, overfitting, and higher computational costs. Hence, we proposed a classification model based on multi-deep feature and support vector machine (SVM) for the classification of CPSL. The proposed system comprises two phases: First, evaluate the 11 CNN model's performance in the deep feature extraction approach with SVM, and then, concatenate the top performed three CNN model's deep features and with the help of SVM to categorize the CPSL. In the second step, 8192 and 12,288 features are obtained by combining binary and triple networks of 4096 features from the top performed CNN model. These features are also given to the SVM classifiers. The SVM results are also evaluated with principal component analysis (PCA) algorithm to the combined feature of 8192 and 12,288. The highest results are obtained with 12,288 features. The experimentation results, the combination of the deep feature of Alexnet, VGG16 and VGG19, achieved the highest accuracy of 91.7% using SVM classifier. As a result, the results show that the proposed methods are a useful tool for CPSL classification. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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