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Found 6 papers, 5 papers with code
Self-supervised motion descriptor for cardiac phase detection in 4D CMR based on discrete vector field estimations
Simultaneously, deep learning-based deformable image registration is able to estimate discrete vector fields which warp one time step of a CMR sequence to the following in a self-supervised manner.
Comparison of Evaluation Metrics for Landmark Detection in CMR Images
In this work, we extended the public ACDC dataset with additional labels of the right ventricular insertion points and compare different variants of a heatmap-based landmark detection pipeline.
Mutually improved endoscopic image synthesis and landmark detection in unpaired image-to-image translation
In this use case, it is of paramount importance to display objects like needles, sutures or instruments consistent in both domains while altering the style to a more tissue-like appearance.
Unsupervised Domain Adaptation from Axial to Short-Axis Multi-Slice Cardiac MR Images by Incorporating Pretrained Task Networks
This is an improvement of $25\%$ in Dice for RV in comparison to direct application on axial slices.
Heatmap-based 2D Landmark Detection with a Varying Number of Landmarks
Mitral valve repair is a surgery to restore the function of the mitral valve.
How well do U-Net-based segmentation trained on adult cardiac magnetic resonance imaging data generalise to rare congenital heart diseases for surgical planning?
Our results confirm that current deep learning models can achieve excellent results (left ventricle dice of $0. 951\pm{0. 003}$/$0. 941\pm{0. 007}$ train/validation) within a single data collection.
