Deep Learning for Whole-Slide Tissue Histopathology Classification: A Comparative Study in the Identification of Dysplastic and Non-Dysplastic Barrett’s Esophagus

Deep Learning for Whole-Slide Tissue Histopathology Classification: A Comparative Study in the Identification of Dysplastic and Non-Dysplastic Barrett’s Esophagus

The gold standard of histopathology for the diagnosis of Barrett’s esophagus (BE) is hindered by inter-observer variability among gastrointestinal pathologists. Deep learning-based approaches have shown promising results in the analysis of whole-slide tissue histopathology images (WSIs). We performe...

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Bibliographic Details
Main Authors: Rasoul Sali, Nazanin Moradinasab, Shan Guleria, Lubaina Ehsan, Philip Fernandes, Tilak U. Shah, Sana Syed, Donald E. Brown
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Journal of Personalized Medicine
Subjects:
deep learning
whole-slide tissue histopathology
feature extraction approaches
Barrett’s esophagus
Online Access:https://www.mdpi.com/2075-4426/10/4/141

Internet

https://www.mdpi.com/2075-4426/10/4/141

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