Melanoma Detection Using Delaunay Triangulation

被引：16

作者：

Pennisi, A. ^{[1
]}

Bloisi, D. D. ^{[1
]}

Nardi, D. ^{[1
]}

Giampetruzzi, A. R. ^{[2
]}

Mondino, C. ^{[3
]}

Facchiano, A. ^{[2
]}

机构：

[1] Univ Roma La Sapienza, Dept Comp Control & Management Engn, Rome, Italy

[2] Ist Dermopat Immacolata IDI IRCCS, Rome, Italy

[3] Cantonal Hosp Bellinzona, Dept Dermatol, Bellinzona, Switzerland

来源：

2015 IEEE 27TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2015) | 2015年

关键词：

Melanoma detection; Dermoscopy images; Automatic segmentation; Border detection; BORDER DETECTION; IMAGES; SEGMENTATION; DIAGNOSIS;

D O I：

10.1109/ICTAI.2015.117

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The detection of malignant lesions in dermoscopic images by using automatic diagnostic tools can help in reducing mortality from melanoma. In this paper, we describe a fully-automatic algorithm for skin lesion segmentation in dermoscopic images. The proposed approach is highly accurate when dealing with benign lesions, while the detection accuracy significantly decreases when melanoma images are segmented. This particular behavior lead us to consider geometrical and color features extracted from the output of our algorithm for classifying melanoma images, achieving promising results.

引用

页码：791 / 798

页数：8

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