Factors affecting the labelling accuracy of brain MRI studies relevant for deep learning abnormality detection

Factors affecting the labelling accuracy of brain MRI studies relevant for deep learning abnormality detection

Unlocking the vast potential of deep learning-based computer vision classification systems necessitates large data sets for model training. Natural Language Processing (NLP)—involving automation of dataset labelling—represents a potential avenue to achieve this. However, many aspects of NLP for data...

Full description

Bibliographic Details
Main Authors: Matthew Benger, David A. Wood, Sina Kafiabadi, Aisha Al Busaidi, Emily Guilhem, Jeremy Lynch, Matthew Townend, Antanas Montvila, Juveria Siddiqui, Naveen Gadapa, Gareth Barker, Sebastian Ourselin, James H. Cole, Thomas C. Booth
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-11-01
Series:Frontiers in Radiology
Subjects:
deep learning
computer vision system
labelling
neuroradiology
MRI
Online Access:https://www.frontiersin.org/articles/10.3389/fradi.2023.1251825/full

Internet

https://www.frontiersin.org/articles/10.3389/fradi.2023.1251825/full

Similar Items