First-Stage Prostate Cancer Identification on Histopathological Images: Hand-Driven versus Automatic Learning

First-Stage Prostate Cancer Identification on Histopathological Images: Hand-Driven versus Automatic Learning

Analysis of histopathological image supposes the most reliable procedure to identify prostate cancer. Most studies try to develop computer aid-systems to face the Gleason grading problem. On the contrary, we delve into the discrimination between healthy and cancerous tissues in its earliest stage, o...

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Bibliographic Details
Main Authors: Gabriel García, Adrián Colomer, Valery Naranjo
Format: Article
Language:English
Published: MDPI AG 2019-04-01
Series:Entropy
Subjects:
gland classification
hand-crafted feature extraction
feature selection
hand-driven learning
deep learning
prostate cancer
histological image
Online Access:https://www.mdpi.com/1099-4300/21/4/356

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https://www.mdpi.com/1099-4300/21/4/356

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