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Found 10 papers, 3 papers with code
Detecting Unforeseen Data Properties with Diffusion Autoencoder Embeddings using Spine MRI data
Our findings highlight the potential of using advanced embedding techniques like DAEs to detect data quality issues and biases in medical imaging datasets.
Whole Heart 3D+T Representation Learning Through Sparse 2D Cardiac MR Images
Cardiac Magnetic Resonance (CMR) imaging serves as the gold-standard for evaluating cardiac morphology and function.
TotalVibeSegmentator: Full Torso Segmentation for the NAKO and UK Biobank in Volumetric Interpolated Breath-hold Examination Body Images
Objectives: To present a publicly available torso segmentation network for large epidemiology datasets on volumetric interpolated breath-hold examination (VIBE) images.
Diff-Def: Diffusion-Generated Deformation Fields for Conditional Atlases
Anatomical atlases are widely used for population analysis.
A Comparative Study of Population-Graph Construction Methods and Graph Neural Networks for Brain Age Regression
We conclude that static graph construction approaches are potentially insufficient for the task of brain age estimation and make recommendations for alternative research directions.
Population-Specific Atlases from Whole Body MRI: Application to the UKBB
Reliable reference data in medical imaging is largely unavailable.
Unlocking the Diagnostic Potential of ECG through Knowledge Transfer from Cardiac MRI
In a qualitative analysis, we demonstrate that our learned ECG embeddings incorporate information from CMR image regions of interest.
Atlas-Based Interpretable Age Prediction In Whole-Body MR Images
We show that the investigation of the full 3D volume of the whole body and the population-wide analysis can give important insights into which body parts play the most important roles in predicting a person's age.
Extended Graph Assessment Metrics for Graph Neural Networks
In this work, we introduce extended graph assessment metrics (GAMs) for regression tasks and continuous adjacency matrices.
Body Fat Estimation from Surface Meshes using Graph Neural Networks
Body fat volume and distribution can be a strong indication for a person's overall health and the risk for developing diseases like type 2 diabetes and cardiovascular diseases.
