Computer-Aided Detection Can Bridge the Skill Gap in Multiple Sclerosis Monitoring

J Am Coll Radiol. 2018 Jan;15(1 Pt A):93-96. doi: 10.1016/j.jacr.2017.06.030. Epub 2017 Jul 29.

Authors

Ariel Dahan¹, Wayland Wang², Frank Gaillard³

Affiliations

¹ St Vincent's Hospital Melbourne, Fitzroy, Australia.
² Department of Radiology, Austin Health, Heidelberg, Australia.
³ Department of Radiology, University of Melbourne, The Royal Melbourne Hospital, Parkville, Australia. Electronic address: frank.gaillard@mh.org.au.

PMID: 28764954
DOI: 10.1016/j.jacr.2017.06.030

No abstract available

Publication types

Randomized Controlled Trial

MeSH terms

Australia
Diagnosis, Computer-Assisted / methods*
Humans
Magnetic Resonance Imaging / methods*
Multiple Sclerosis / diagnostic imaging*
Neuroimaging / methods*
Proof of Concept Study
Sensitivity and Specificity
Software