Toward More Transparent and Accurate Cancer Diagnosis With an Unsupervised CAE Approach

Toward More Transparent and Accurate Cancer Diagnosis With an Unsupervised CAE Approach

According to the Global Cancer Observatory, 2020, breast cancer is the most prevalent cancer type in both genders (11.7%), while prostate cancer is the second most common cancer type in men (14.1%). In digital pathology, Content-Based Medical Image Retrieval (CBMIR) is a powerf...

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Bibliographic Details
Main Authors: Zahra Tabatabaei, Adrian Colomer, Javier Oliver Moll, Valery Naranjo
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Histopathological images
content-based medical image retrieval (CBMIR)
convolutional auto encoder
unsupervised learning
whole slide images (WSIs)
digital pathology
Online Access:https://ieeexplore.ieee.org/document/10363200/

Internet

https://ieeexplore.ieee.org/document/10363200/

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