Share Email Print
cover

Proceedings Paper

Melanoma detection on dermoscopic images using superpixels segmentation and shape-based features
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

In this work, we present a shape-based approach to automatic skin lesion segmentation and classification in dermoscopic images. We aim to differentiate three types of lesion 1) common nevi, 2) atypical nevi, and 3) melanomas by exploring the morphology features of segmented skin lesions. Our method is an attempt to design a computer-aided ABCDEs of melanoma, where the Asymmetry and Border components are estimated using morphological features. The lesions are first segmented using a super-pixel merging strategy with an RGB criterion. Later, the segmentation method was evaluated on the PH2 dataset, and compared with other state-of- the-art skin segmentation methods. The classification was also conducted on the PH2 dataset through a 10-fold cross-validation set-up with a training and testing set partition of 90% and 10% respectively. We employed logistic regression, SVM and a neural network as classification algorithms. The best performances was 86.5% on average with the neural network.

Paper Details

Date Published: 3 January 2020
PDF: 9 pages
Proc. SPIE 11330, 15th International Symposium on Medical Information Processing and Analysis, 1133018 (3 January 2020); doi: 10.1117/12.2545300
Show Author Affiliations
Diego Patiño, Univ. Nacional de Colombia Sede Medellín (Colombia)
Alberto M. Ceballos-Arroyo, Univ. Nacional de Colombia Sede Medellín (Colombia)
Jairo A. Rodriguez-Rodriguez, Univ. Nacional de Colombia Sede Medellín (Colombia)
German Sanchez-Torres, Univ. del Magdalena (Colombia)
John W. Branch-Bedoya, Univ. Nacional de Colombia Sede Medellín (Colombia)


Published in SPIE Proceedings Vol. 11330:
15th International Symposium on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore; Jorge Brieva, Editor(s)

© SPIE. Terms of Use
Back to Top
PREMIUM CONTENT
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?
close_icon_gray