85 citations · 85 across the 5 of their papers we have counts for
9 papers
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…
Detection, growth quantification and malignancy prediction of pulmonary nodules using deep convolutional networks in follow-up CT scans
Xavier Rafael-Palou, Anton Aubanell, Mario Ceresa +3
We address the problem of supporting radiologists in the longitudinal management of lung cancer. Therefore, we proposed a deep learning pipeline, composed of four stages that compl…
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,…
Pulmonary Nodule Malignancy Classification Using its Temporal Evolution with Two-Stream 3D Convolutional Neural Networks
Xavier Rafael-Palou, Anton Aubanell, Ilaria Bonavita +4
Nodule malignancy assessment is a complex, time-consuming and error-prone task. Current clinical practice requires measuring changes in size and density of the nodule at different…
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…