Entropy-Based Skin Lesion Segmentation Using Stochastic Fractal Search Algorithm

被引：0

作者：

Bingol, Okan ^{[1
]}

Pacaci, Serdar ^{[2
]}

Guvenc, Ugur ^{[3
]}

机构：

[1] Isparta Univ Appl Sci, Dept Elect & Elect Engn, Isparta, Turkey

[2] Suleyman Demirel Univ, Dept Informat Technol, Isparta, Turkey

[3] Duzce Univ, Dept Elect & Elect Engn, Duzce, Turkey

来源：

ARTIFICIAL INTELLIGENCE AND APPLIED MATHEMATICS IN ENGINEERING PROBLEMS | 2020年 / 43卷

关键词：

Lesion segmentation; Entropy; Stochastic fractal search;

D O I：

10.1007/978-3-030-36178-5_69

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Skin cancer is a type of cancer that attracts attention with the increasing number of cases. Detection of the lesion area on the skin has an important role in the diagnosis of dermatologists. In this study, 5 different entropy methods such as Kapur, Tsallis, Havrda and Charvat, Renyi and Minimum Cross were applied to determine the lesion area on dermoscopic images. Stochastic fractal search algorithm was used to determine threshold values with these 5 methods. PH2 data set was used for skin lesion images.

引用

页码：801 / 811

页数：11

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