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Machine Learning in Neurooncology Imaging: From Study Request to Diagnosis and Treatment

Authors :
Javier Villanueva-Meyer
Janine M. Lupo
Adam E. Flanders
Marc D. Kohli
Christopher P. Hess
Peter Chang
Source :
AJR. American journal of roentgenology. 212(1)
Publication Year :
2018

Abstract

Machine learning has potential to play a key role across a variety of medical imaging applications. This review seeks to elucidate the ways in which machine learning can aid and enhance diagnosis, treatment, and follow-up in neurooncology.Given the rapid pace of development in machine learning over the past several years, a basic proficiency of the key tenets and use cases in the field is critical to assessing potential opportunities and challenges of this exciting new technology.

Details

ISSN :
15463141
Volume :
212
Issue :
1
Database :
OpenAIRE
Journal :
AJR. American journal of roentgenology
Accession number :
edsair.doi.dedup.....983f24ad99e5956ca707906444c40425