Fast fully automatic skin lesions segmentation probabilistic with Parzen window

Cutaneous melanoma accounts for over 90% of all melanoma, causing up to 55,500 annual deaths. However, it is a potentially curable type of cancer. Since melanoma is potentially curable, the disease’s mortality rate is directly linked to late detection. This work proposes an approach that presents th...

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Bibliographic Details
Published in:	Computerized medical imaging and graphics Vol. 85; p. 101774
Main Authors:	Chagas, João V. Souza das, Ivo, Roberto F., Guimarães, Matheus T., de A. Rodrigues, Douglas, de S. Rebouças, Elizângela, Rebouças Filho, Pedro P.
Format:	Journal Article
Language:	English
Published:	United States Elsevier Ltd 01-10-2020 Elsevier Science Ltd
Subjects:	Datasets Image processing Image segmentation Lesions Melanoma Melanoma skin Parzen window Probability density Skin diseases Skin lesions Probability density Melanoma skin Parzen window
Online Access:	Get full text
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Summary:	Cutaneous melanoma accounts for over 90% of all melanoma, causing up to 55,500 annual deaths. However, it is a potentially curable type of cancer. Since melanoma is potentially curable, the disease’s mortality rate is directly linked to late detection. This work proposes an approach that presents the balance between time and efficiency. This paper proposes the method of fast and automatic segmentation of skin lesions using probabilistic characteristics with the Parzen window (SPPW). The results obtained by the method were based on PH2 and ISIC datasets. The SPPW approach reached the following averages between the two datasets Specificity of 98.55%, Accuracy of 95.48%, Dice of 91.12%, Sensitivity of 88.45%, Mattheus of 87.86%, and Jaccard Index of 84.90%. The highlights of the proposed method are its short average segmentation time per image, and its metrics values, which are often higher than the ones obtained by other methods. Therefore, the SPPW method of segmentation is a quick, viable, and easily accessible option to aid in the diagnosis of diseased skin. •Segmentation of skin lesions using the Parzen probabilistic window (SSPPW).•The medical necessity for easy access efficient methods justifies the approach.•Surface smoothing and the Hamilton–Jacobi equation are contributions of the method.•The method is stable, automatic, and fast for skin lesions segmentation.•Higher values on metrics like Dice coefficient, Matthew coefficient, and Jaccard.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	0895-6111 1879-0771
DOI:	10.1016/j.compmedimag.2020.101774