85 citations · 85 across the 5 of their papers we have counts for
5 papers · 1 filter
Unsupervised Segmentation of Fetal Brain MRI using Deep Learning Cascaded Registration
Valentin Comte, Mireia Alenya, Andrea Urru +10
Accurate segmentation of fetal brain magnetic resonance images is crucial for analyzing fetal brain development and detecting potential neurodevelopmental abnormalities. Traditiona…
BabyNet: Reconstructing 3D faces of babies from uncalibrated photographs
Araceli Morales, Antonio R. Porras, Marius George Linguraru +2
We present a 3D face reconstruction system that aims at recovering the 3D facial geometry of babies from uncalibrated photographs, BabyNet. Since the 3D facial geometry of babies d…
An Uncertainty-aware Hierarchical Probabilistic Network for Early Prediction, Quantification and Segmentation of Pulmonary Tumour Growth
Xavier Rafael-Palou, Anton Aubanell, Mario Ceresa +3
Early detection and quantification of tumour growth would help clinicians to prescribe more accurate treatments and provide better surgical planning. However, the multifactorial an…
Survey on 3D face reconstruction from uncalibrated images
Araceli Morales, Gemma Piella, Federico M. Sukno
Recently, a lot of attention has been focused on the incorporation of 3D data into face analysis and its applications. Despite providing a more accurate representation of the face,…
Medical-based Deep Curriculum Learning for Improved Fracture Classification
Amelia Jiménez-Sánchez, Diana Mateus, Sonja Kirchhoff +5
Current deep-learning based methods do not easily integrate to clinical protocols, neither take full advantage of medical knowledge. In this work, we propose and compare several st…