Publications

@article{gonzalez-castro_automatic_2015-1,

title = {Automatic classification of skin lesions using geometrical measurements of adaptive neighborhoods and local binary patterns},

author = {Víctor González-Castro and Johan Debayle and Yanal Wazaefi and Mehdi Rahim and Caroline Gaudy-Marqueste and Jean-Jacques Grob and Bernard Fertil},

url = {https://ieeexplore.ieee.org/abstract/document/7351095},

year  = {2015},

date = {2015-01-01},

urldate = {2015-01-01},

journal = {2015 IEEE International Conference on Image Processing (ICIP)},

pages = {1722–1726},

abstract = {This paper presents a method for characterizing and classifying skin lesions in dermoscopic images to detect melanoma. It uses Local Binary Patterns (LBPs) on geometrical feature maps derived from General Adaptive Neighborhoods (GAN). An Artificial Neural Network evaluates performance, showing that the GAN-based approach outperforms classical LBPs and dermatologists' predictions in ROC curve analysis.},

note = {Publisher: IEEE},

keywords = {dermoscopic imaging, LBP, local binary pattern, skin cancer detection},

pubstate = {published},

tppubtype = {article}

}