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Found 3 papers, 2 papers with code
MiMICRI: Towards Domain-centered Counterfactual Explanations of Cardiovascular Image Classification Models
We conclude with a discussion on the generalizability and trustworthiness of the MiMICRI framework, as well as the implications of our findings on the development of domain-centered XAI methods for model interpretability in healthcare contexts.
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.
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.
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