Artificial intelligence–based rapid brain volumetry substantially improves differential diagnosis in dementia

Artificial intelligence–based rapid brain volumetry substantially improves differential diagnosis in dementia

Abstract Introduction This study evaluates the clinical value of a deep learning–based artificial intelligence (AI) system that performs rapid brain volumetry with automatic lobe segmentation and age‐ and sex‐adjusted percentile comparisons. Methods Fifty‐five patients—17 with Alzheimer's disea...

Full description

Saved in:
Bibliographic Details
Main Authors: Jan Rudolph, Johannes Rueckel, Jörg Döpfert, Wen Xin Ling, Jens Opalka, Christian Brem, Nina Hesse, Maria Ingenerf, Vanessa Koliogiannis, Olga Solyanik, Boj F. Hoppe, Hanna Zimmermann, Wilhelm Flatz, Robert Forbrig, Maximilian Patzig, Boris‐Stephan Rauchmann, Robert Perneczky, Oliver Peters, Josef Priller, Anja Schneider, Klaus Fliessbach, Andreas Hermann, Jens Wiltfang, Frank Jessen, Emrah Düzel, Katharina Buerger, Stefan Teipel, Christoph Laske, Matthis Synofzik, Annika Spottke, Michael Ewers, Peter Dechent, John‐Dylan Haynes, Johannes Levin, Thomas Liebig, Jens Ricke, Michael Ingrisch, Sophia Stoecklein
Format: Article
Language:English
Published: Wiley 2024-10-01
Series:Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring
Subjects:
Alzheimer's disease
artificial intelligence
brain volumetry
clinical cohorts
frontotemporal dementia
Online Access:https://doi.org/10.1002/dad2.70037
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1002/dad2.70037

Similar Items