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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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Journal ArticleDOI
Multiview diffeomorphic registration: application to motion and strain estimation from 3D echocardiography.
Gemma Piella,Mathieu De Craene,Constantine Butakoff,Vicente Grau,Cheng Yao,S Nedjati-Gilani,Graeme P. Penney,Alejandro F. Frangi,Alejandro F. Frangi +8 more
TL;DR: A multiview diffeomorphic registration strategy that enforces smoothness and consistency in the spatiotemporal domain by modeling the 4D velocity field continuously in space and time is proposed.
Book ChapterDOI
Building an Ensemble of Complementary Segmentation Methods by Exploiting Probabilistic Estimates
TL;DR: The proposed ensemble segmentation method outperforms the rest of participating methods in most of the structures of the NeoBrainS12 Challenge on neonatal brain segmentation and shows that sacrificing invariance to registration errors improves the performance of the intensity-based method.
Journal ArticleDOI
Cortical folding alterations in fetuses with isolated non-severe ventriculomegaly.
Oualid Benkarim,N.M. Hahner,Gemma Piella,Eduard Gratacós,Miguel Ángel González Ballester,Elisenda Eixarch,Gerard Sanroma +6 more
TL;DR: It is suggested that INSVM is an indicator of altered cortical development, and moreover, cortical regions with reduced folding constitute potential prognostic biomarkers to be used in follow-up studies to decipher the outcome of INSVM fetuses.
Journal ArticleDOI
Diffusion maps for multimodal registration.
TL;DR: This work proposes to register multimodal images by using diffusion maps to describe the geometric and spectral properties of the data, and shows that the proposed approach achieved higher accuracy than the conventional approach using mutual information.
Journal ArticleDOI
Patient-specific estimation of detailed cochlear shape from clinical CT images.
H. Martin Kjer,Jens Fagertun,Wilhelm Wimmer,Nicolas Gerber,Sergio Vera,Livia Barazzetti,Nerea Mangado,Mario Ceresa,Gemma Piella,Thomas Stark,Martin Stauber,Mauricio Reyes,Stefan Weber,Marco Caversaccio,Miguel Ángel González Ballester,Miguel Ángel González Ballester,Rasmus Reinhold Paulsen +16 more
TL;DR: This work develops and test a method for estimation of the detailed patient-specific cochlear shape from CT images, and presents the process of building and using the cochlea statistical deformation model (SDM).