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Found 6 papers, 4 papers with code
Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data
We then show improved downstream performance on fiber tractography measures on the Tractometer benchmark dataset.
Q-space Conditioned Translation Networks for Directional Synthesis of Diffusion Weighted Images from Multi-modal Structural MRI
Further, such approaches can restrict downstream usage of variably sampled DWIs for usages including the estimation of microstructural indices or tractography.
Learning to Compare Longitudinal Images
For example, normalizing for nuisance variation might be hard in settings where there are a lot of idiosyncratic changes.
Empirical Analysis of a Segmentation Foundation Model in Prostate Imaging
Most state-of-the-art techniques for medical image segmentation rely on deep-learning models.
A Framework for Interpretability in Machine Learning for Medical Imaging
To answer these questions, we identify a need to formalize the goals and elements of interpretability in MLMI.
Robust Learning via Conditional Prevalence Adjustment
CoPA assumes that (1) generation mechanism is stable, i. e. label Y and confounding variable(s) Z generate X, and (2) the unstable conditional prevalence in each site E fully accounts for the unstable correlations between X and Y .
