piNET–An Automated Proliferation Index Calculator Framework for Ki67 Breast Cancer Images

piNET–An Automated Proliferation Index Calculator Framework for Ki67 Breast Cancer Images

In this work, a novel proliferation index (PI) calculator for Ki67 images called piNET is proposed. It is successfully tested on four datasets, from three scanners comprised of patches, tissue microarrays (TMAs) and whole slide images (WSI), representing a diverse multi-centre dataset for evaluating...

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Bibliographic Details
Main Authors: Rokshana Stephny Geread, Abishika Sivanandarajah, Emily Rita Brouwer, Geoffrey A. Wood, Dimitrios Androutsos, Hala Faragalla, April Khademi
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Cancers
Subjects:
breast cancer
deep learning
digital pathology
hematoxylin
Ki67
proliferation index
Online Access:https://www.mdpi.com/2072-6694/13/1/11

Internet

https://www.mdpi.com/2072-6694/13/1/11

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