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Found 3 papers, 2 papers with code
Unsupervised Analysis of Alzheimer's Disease Signatures using 3D Deformable Autoencoders
With the increasing incidence of neurodegenerative diseases such as Alzheimer's Disease (AD), there is a need for further research that enhances detection and monitoring of the diseases.
Simulation of acquisition shifts in T2 Flair MR images to stress test AI segmentation networks
Experiments comprise the validation of the simulated images by real MR scans and example stress tests on state-of-the-art MS lesion segmentation networks to explore a generic model function to describe the F1 score in dependence of the contrast-affecting sequence parameters echo time (TE) and inversion time (TI).
Improving accuracy and uncertainty quantification of deep learning based quantitative MRI using Monte Carlo dropout
Dropout is conventionally used during the training phase as regularization method and for quantifying uncertainty in deep learning.
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