Title of article
Performance of a dermoscopy-based computer vision system for the diagnosis of pigmented skin lesions compared with visual evaluation by experienced dermatologists
Author/Authors
Zortea، نويسنده , , Maciel and Schopf، نويسنده , , Thomas R. and Thon، نويسنده , , Kevin and Geilhufe، نويسنده , , Marc and Hindberg، نويسنده , , Kristian and Kirchesch، نويسنده , , Herbert and Mّllersen، نويسنده , , Kajsa and Schulz، نويسنده , , Jِrn and Skrّvseth، نويسنده , , Stein Olav and Godtliebsen، نويسنده , , Fred، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2014
Pages
14
From page
13
To page
26
Abstract
AbstractBackground
often difficult to differentiate early melanomas from benign melanocytic nevi even by expert dermatologists, and the task is even more challenging for primary care physicians untrained in dermatology and dermoscopy. A computer system can provide an objective and quantitative evaluation of skin lesions, reducing subjectivity in the diagnosis.
ive
jective is to make a low-cost computer aided diagnostic tool applicable in primary care based on a consumer grade camera with attached dermatoscope, and compare its performance to that of experienced dermatologists.
s and materials
pose several new image-derived features computed from automatically segmented dermoscopic pictures. These are related to the asymmetry, color, border, geometry, and texture of skin lesions. The diagnostic accuracy of the system is compared with that of three dermatologists.
s
data set of 206 skin lesions, 169 benign and 37 melanomas, the classifier was able to provide competitive sensitivity (86%) and specificity (52%) scores compared with the sensitivity (85%) and specificity (48%) of the most accurate dermatologist using only dermoscopic images.
sion
w that simple statistical classifiers can be trained to provide a recommendation on whether a pigmented skin lesion requires biopsy to exclude skin cancer with a performance that is comparable to and exceeds that of experienced dermatologists.
Keywords
Pigmented skin lesions , Dermoscopy , Supervised classification , Skin cancer detection , melanoma , computer-aided diagnosis
Journal title
Artificial Intelligence In Medicine
Serial Year
2014
Journal title
Artificial Intelligence In Medicine
Record number
1837325
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