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Document type:
Zeitschriftenaufsatz 
Author(s):
Baur, C.; Wiestler, B.; Albarqouni, S.; Navab, N. 
Title:
Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI 
Abstract:
Brain pathologies can vary greatly in size and shape, ranging from few pixels (i.e. MS lesions) to large, space-occupying tumors. Recently proposed Autoencoder-based methods for unsupervised anomaly segmentation in brain MRI have shown promising performance, but face difficulties in modeling distributions with high fidelity, which is crucial for accurate delineation of particularly small lesions. Here, similar to these previous works, we model the distribution of healthy brain MRI to localize pa...    »
 
Keywords:
Anomaly Segmentation,Anomaly Detection,Unsupervised,Laplacian Pyramid,Scale Space,Autoencoders,Brain MRI,Variational Autoencoders,Deep Learning,MICCAI 
Journal title:
arXiv preprint arXiv:2006.12852 
Year:
2020