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A New Optical Density Granulometry-Based Descriptor for the Classification of Prostate Histological Images Using Shallow and Deep Gaussian Processes

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A New Optical Density Granulometry-Based Descriptor for the Classification of Prostate Histological Images Using Shallow and Deep Gaussian Processes

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Esteban, AE.; López-Pérez, M.; Colomer, A.; Sales, MA.; Molina, R.; Naranjo Ornedo, V. (2019). A New Optical Density Granulometry-Based Descriptor for the Classification of Prostate Histological Images Using Shallow and Deep Gaussian Processes. Computer Methods and Programs in Biomedicine. 178:303-317. https://doi.org/10.1016/j.cmpb.2019.07.003

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/151053

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Title: A New Optical Density Granulometry-Based Descriptor for the Classification of Prostate Histological Images Using Shallow and Deep Gaussian Processes
Author: Esteban, A. E. López-Pérez, Miguel Colomer, Adrián Sales, Maria A. Molina, Rafael Naranjo Ornedo, Valeriana
UPV Unit: Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions
Issued date:
Abstract:
[EN] Background and objective Prostate cancer is one of the most common male tumors. The increasing use of whole slide digital scanners has led to an enormous interest in the application of machine learning techniques to ...[+]
Subjects: Prostate cancer , Histopathological Images , Gaussian Processes , Variational Inference , Granulometries , Deep Gaussian Processes
Copyrigths: Reserva de todos los derechos
Source:
Computer Methods and Programs in Biomedicine. (issn: 0169-2607 )
DOI: 10.1016/j.cmpb.2019.07.003
Publisher:
Elsevier
Publisher version: https://doi.org/10.1016/j.cmpb.2019.07.003
Project ID:
AGENCIA ESTATAL DE INVESTIGACION/DPI2016-77869-C2-1-R
Thanks:
This work was supported by the Ministerio de Economia y Competitividad through project DPI2016-77869. The Titan V used for this research was donated by the NVIDIA Corporation
Type: Artículo

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