Detection of pigment network in dermoscopy images using supervised machine learning and structural analysis
Cargando...
Fecha
2014-01
Título de la revista
ISSN de la revista
Título del volumen
Editor
Resumen
By means of this study, a detection algorithm for the "pigment network" in dermoscopic images is presented, one of the most relevant indicators in the diagnosis of melanoma. The design of the algorithm consists of two blocks. In the first one, a machine learning process is carried out, allowing the generation of a set of rules which, when applied over the image, permit the construction of a mask with the pixels candidates to be part of the pigment network. In the second block, an analysis of the structures over this mask is carried out, searching for those corresponding to the pigment network and making the diagnosis, whether it has pigment network or not, and also generating the mask corresponding to this pattern, if any. The method was tested against a database of 220 images, obtaining 86% sensitivity and 81.67% specificity, which proves the reliability of the algorithm. © 2013 The Authors.
Palabras clave
Machine learning
Melanoma
Pigment network
Reticular pattern
Structural analysis
Melanoma
Pigment network
Reticular pattern
Structural analysis
Descripción
Materias
Cita
García Arroyo, J. L., & García Zapirain, B. (2014). Detection of pigment network in dermoscopy images using supervised machine learning and structural analysis. Computers in Biology and Medicine, 44(1), 144-157. https://doi.org/10.1016/J.COMPBIOMED.2013.11.002