Uncertainty-Guided Active Learning for Access Route Segmentation and Planning in Transcatheter Aortic Valve Implantation
Published in Journal of Imaging, MDPI, 2025
This study introduces an annotation-efficient active learning pipeline for 3D segmentation and automated diameter quantification in CMR-based TAVI planning.
Authors: Mahdi Islam, Musarrat Tabassum, Agnes Mayr, Christian Kremser, Markus Haltmeier, Enrique Almar-Munoz
Venue: Journal of Imaging, MDPI
Recommended citation: Mahdi Islam, Musarrat Tabassum, Agnes Mayr, Christian Kremser, Markus Haltmeier, Enrique Almar-Munoz. "Uncertainty-Guided Active Learning for Access Route Segmentation and Planning in Transcatheter Aortic Valve Implantation." *Journal of Imaging*, vol. 11, no. 9, 318, 2025. https://doi.org/10.3390/jimaging11090318.
Recommended citation: Mahdi Islam, Musarrat Tabassum, Agnes Mayr, Christian Kremser, Markus Haltmeier, Enrique Almar-Munoz. "Uncertainty-Guided Active Learning for Access Route Segmentation and Planning in Transcatheter Aortic Valve Implantation." *Journal of Imaging*, vol. 11, no. 9, 318, 2025. https://doi.org/10.3390/jimaging11090318.