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Found 3 papers, 2 papers with code
Self-supervised Learning of Dense Hierarchical Representations for Medical Image Segmentation
This paper demonstrates a self-supervised framework for learning voxel-wise coarse-to-fine representations tailored for dense downstream tasks.
An Uncertainty-Aware, Shareable and Transparent Neural Network Architecture for Brain-Age Modeling
The deviation between chronological age and age predicted from neuroimaging data has been identified as a sensitive risk-marker of cross-disorder brain changes, growing into a cornerstone of biological age-research.
Predicting brain-age from raw T 1 -weighted Magnetic Resonance Imaging data using 3D Convolutional Neural Networks
For comparison, state-of-the-art models using preprocessed neuroimaging data are trained and validated on the same samples.
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