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Document type:
Konferenzbeitrag 
Author(s):
Baur, C.; Wiestler, B.; Albarqouni, S.; Navab, N. 
Title:
Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain MR Images 
Abstract:
Reliably modeling normality and differentiating abnormal appearances from normal cases is a very appealing approach for detecting pathologies in medical images. A plethora of such unsupervised anomaly detection approaches has been made in the medical domain, based on statistical methods, content-based retrieval, clustering and recently also deep learning. Previous approaches towards deep unsupervised anomaly detection model local patches of normal anatomy with variants of Autoencoders or GANs, a...    »
 
Keywords:
miccai,Brainles,Brain lesion workshop,autoencoder,VAEGAN,VAE-GAN,GAN,VAE,brain,MRI,MSLesion,segmentation,unsupervised,deeplearning 
Book / Congress title:
International MICCAI Brainlesion Workshop 
Organization:
Springer 
Year:
2018