Which data subset should be augmented for deep learning? a simulation study using urothelial cell carcinoma histopathology images

Which data subset should be augmented for deep learning? a simulation study using urothelial cell carcinoma histopathology images

Abstract Background Applying deep learning to digital histopathology is hindered by the scarcity of manually annotated datasets. While data augmentation can ameliorate this obstacle, its methods are far from standardized. Our aim was to systematically explore the effects of skipping data augmentatio...

Full description

Bibliographic Details
Main Authors: Yusra A. Ameen, Dalia M. Badary, Ahmad Elbadry I. Abonnoor, Khaled F. Hussain, Adel A. Sewisy
Format: Article
Language:English
Published: BMC 2023-03-01
Series:BMC Bioinformatics
Subjects:
Convolutional neural network
Data augmentation
Deep learning
Histopathology
Urothelial cell carcinoma
Online Access:https://doi.org/10.1186/s12859-023-05199-y

Internet

https://doi.org/10.1186/s12859-023-05199-y

Similar Items