3E-Net: Entropy-Based Elastic Ensemble of Deep Convolutional Neural Networks for Grading of Invasive Breast Carcinoma Histopathological Microscopic Images

3E-Net: Entropy-Based Elastic Ensemble of Deep Convolutional Neural Networks for Grading of Invasive Breast Carcinoma Histopathological Microscopic Images

Automated grading systems using deep convolution neural networks (DCNNs) have proven their capability and potential to distinguish between different breast cancer grades using digitized histopathological images. In digital breast pathology, it is vital to measure how confident a DCNN is in grading u...

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Bibliographic Details
Main Authors: Zakaria Senousy, Mohammed M. Abdelsamea, Mona Mostafa Mohamed, Mohamed Medhat Gaber
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Entropy
Subjects:
breast cancer
histopathological images
entropy
uncertainty quantification
elastic ensemble
dynamic ensemble
Online Access:https://www.mdpi.com/1099-4300/23/5/620

Internet

https://www.mdpi.com/1099-4300/23/5/620

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