Publications by authors named "Carla Sendra-Balcells"
Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&Ms Challenge.
IEEE J Biomed Health Inform
July 2023
In recent years, several deep learning models have been proposed to accurately quantify and diagnose cardiac pathologies. These automated tools heavily rely on the accurate segmentation of cardiac structures in MRI images. However, segmentation of the right ventricle is challenging due to its highly complex shape and ill-defined borders.
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- Most AI advancements in healthcare have primarily taken place in wealthy countries, creating a gap in low-resource areas like Sub-Saharan Africa, where high perinatal mortality rates could be alleviated with better medical imaging.
- Deep learning models have been proposed for fetal ultrasound diagnosis, but their effectiveness in resource-poor settings remains unproven due to different equipment and data availability.
- This research explores ways to adapt high-resource AI models for low-resource environments, demonstrating that transfer learning can improve model performance in African countries by combining small local samples with larger datasets from developed nations.
Background: The domain generalization problem has been widely investigated in deep learning for non-contrast imaging over the last years, but it received limited attention for contrast-enhanced imaging. However, there are marked differences in contrast imaging protocols across clinical centers, in particular in the time between contrast injection and image acquisition, while access to multi-center contrast-enhanced image data is limited compared to available datasets for non-contrast imaging. This calls for new tools for generalizing single-domain, single-center deep learning models across new unseen domains and clinical centers in contrast-enhanced imaging.
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