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2017 IEEE 2nd Ecuador Technical Chapters Meeting, ETCM 2017(1)
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Automatic design of window operators for the segmentation of the prostate gland in magnetic resonance images
Conference ObjectAbstract: W-operators are nonlinear image operators that are translation invariant and locally defined insidePalabras claves:Feed-forward neural network, magnetic resonance, Prostate gland, segmentation, W-operatorAutores:Ballarin V.L., Brun M., Marco E. BenalcázarFuentes:googlescopusAutomatic segmentation of exudates in ocular images using ensembles of aperture filters and logistic regression
Conference ObjectAbstract: Hard and soft exudates are the main signs of diabetic macular edema (DME). The segmentation of bothPalabras claves:Autores:Ballarin V.L., Brun M., Marco E. BenalcázarFuentes:googlescopus2D semantic segmentation of the prostate gland in magnetic resonance images using convolutional neural networks
Conference ObjectAbstract: Convolutional Neural Networks is one of the most commonly used methods for automatic prostate segmenPalabras claves:Central Gland, convolutional neural networks, Encoder-Classifier, Encoder-Decoder, MRIs, NCI-ISBI 2013, Peripheral Zone, Prostate Segmentation, U-net, VGG16Autores:Marco E. Benalcázar, Silvia P. VacacelaFuentes:googlescopusMammogram classification using back-propagation neural networks and texture feature descriptors
Conference ObjectAbstract: Breast cancer has an important incidence in women worldwide. Early diagnosis of this illness plays aPalabras claves:Artificial Neural Network (ANN), Breast Cancer, classification, Cross validation, Gray level co-ocurrence matrix (GLCM), Mammography, pattern recognition, Texture analysisAutores:Conci A., Eduardo Tusa, Marco E. Benalcázar, María Perez, Wilmer Rivas AsanzaFuentes:scopus