Generalisability of fetal ultrasound deep learning models to low-resource imaging settings in five African countries

no code implementations • 20 Sep 2022 • Carla Sendra-Balcells, Víctor M. Campello, Jordina Torrents-Barrena, Yahya Ali Ahmed, Mustafa Elattar, Benard Ohene Botwe, Pempho Nyangulu, William Stones, Mohammed Ammar, Lamya Nawal Benamer, Harriet Nalubega Kisembo, Senai Goitom Sereke, Sikolia Z. Wanyonyi, Marleen Temmerman, Eduard Gratacós, Elisenda Bonet, Elisenda Eixarch, Kamil Mikolaj, Martin Grønnebæk Tolsgaard, Karim Lekadir

This framework shows promise for building new AI models generalisable across clinical centres with limited data acquired in challenging and heterogeneous conditions and calls for further research to develop new solutions for usability of AI in countries with less resources.

Transfer Learning

Domain generalization in deep learning for contrast-enhanced imaging

no code implementations • 14 Oct 2021 • Carla Sendra-Balcells, Víctor M. Campello, Carlos Martín-Isla, David Viladés, Martín L. Descalzo, Andrea Guala, José F. Rodríguez-Palomares, Karim Lekadir

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.

Anatomy Data Augmentation +4

Combining Multi-Sequence and Synthetic Images for Improved Segmentation of Late Gadolinium Enhancement Cardiac MRI

no code implementations • 3 Sep 2019 • Víctor M. Campello, Carlos Martín-Isla, Cristian Izquierdo, Steffen E. Petersen, Miguel A. González Ballester, Karim Lekadir

Second, a deep learning model is trained for segmentation with different combinations of original, augmented and synthetic sequences.

Cardiac Segmentation Data Augmentation +4