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Document type:
Journal Article 
Author(s):
Baur, Christoph; Wiestler, Benedikt; Muehlau, Mark; Zimmer, Claus; Navab, Nassir; Albarqouni, Shadi 
Title:
Modeling Healthy Anatomy with Artificial Intelligence for Unsupervised Anomaly Detection in Brain MRI. 
Abstract:
Purpose: To develop an unsupervised deep learning model on MR images of normal brain anatomy to automatically detect deviations indicative of pathologic states on abnormal MR images. Materials and Methods: In this retrospective study, spatial autoencoders with skip-connections (which can learn to compress and reconstruct data) were leveraged to learn the normal variability of the brain from MR scans of healthy individuals. A total of 100 normal, in-house MR scans were used for training. Subseque...    »
 
Journal title abbreviation:
Radiol Artif Intell 
Year:
2021 
Journal volume:
Journal issue:
Fulltext / DOI:
TUM Institution:
Fachgebiet Neuroradiologie (Prof. Zimmer)