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Gemma Piella
Researcher at Pompeu Fabra University
Publications - 158
Citations - 5510
Gemma Piella is an academic researcher from Pompeu Fabra University. The author has contributed to research in topics: Computer science & Segmentation. The author has an hindex of 25, co-authored 143 publications receiving 4411 citations. Previous affiliations of Gemma Piella include Autonomous University of Barcelona & Polytechnic University of Catalonia.
Papers
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Book ChapterDOI
Atlas-based quantification of myocardial motion abnormalities: added-value for the understanding of CRT outcome?
Nicolas Duchateau,Mathieu De Craene,Gemma Piella,Corné Hoogendoorn,Etelvino Silva,Adelina Doltra,Lluís Mont,Ma Angeles Castel,Josep Brugada,Marta Sitges,Alejandro F. Frangi +10 more
TL;DR: An atlas of normal motion from 21 healthy volunteers is built to which 88 CRT candidates are compared before and after the therapy, and results correlate with recent clinical hypothesis about CRT response.
Book ChapterDOI
Characterization of Myocardial Velocities by Multiple Kernel Learning: Application to Heart Failure with Preserved Ejection Fraction
Sergio Sanchez-Martinez,Nicolas Duchateau,Bart Bijnens,Tamas Erdei,Alan G. Fraser,Gemma Piella +5 more
TL;DR: In this article, an unsupervised manifold learning approach was proposed to improve the characterization of myocardial velocities in the context of heart failure with preserved ejection fraction (HFPEF) by combining multiple descriptors.
Journal ArticleDOI
Integration of Multi-Plane Tissue Doppler and B-Mode Echocardiographic Images for Left Ventricular Motion Estimation
Antonio R. Porras,Martino Alessandrini,Oana Mirea,Jan D'hooge,Alejandro F. Frangi,Gemma Piella +5 more
TL;DR: A method to estimate the motion field from multi-plane echocardiographic images of the left ventricle, which are acquired simultaneously during a single cardiac cycle, using a diffeomorphic continuous spatio-temporal transformation model with a spherical data representation for a better interpolation in the circumferential direction.
Journal ArticleDOI
Reconstruction of the fetus face from three-dimensional ultrasound using a newborn face statistical shape model
Antoni Alomar,Araceli Morales,Kilian Vellvé,Antonio R. Porras,Fatima Crispi,Marius George Linguraru,Gemma Piella,Federico M. Sukno +7 more
TL;DR: In this paper , a statistical morphable model of newborn faces, the BabyFM, was used for fetal face reconstruction from 3D US images, which can aid in in-utero diagnosis for conditions that involve facial dysmorphology.
Posted Content
Re-Identification and Growth Detection of Pulmonary Nodules without Image Registration Using 3D Siamese Neural Networks
Xavier Rafael-Palou,Anton Aubanell,Ilaria Bonavita,Mario Ceresa,Gemma Piella,Vicent J. Ribas,Miguel Ángel González Ballester +6 more
TL;DR: In this article, a 3D siamese neural network was used to detect, match, and predict nodule growth given pairs of CT scans of the same patient without the need for image registration.