M
Miguel Ángel González Ballester
Researcher at Pompeu Fabra University
Publications - 218
Citations - 4320
Miguel Ángel González Ballester 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 194 publications receiving 2913 citations. Previous affiliations of Miguel Ángel González Ballester include T-Systems & Catalan Institution for Research and Advanced Studies.
Papers
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Journal ArticleDOI
Learning to combine complementary segmentation methods for fetal and 6-month infant brain MRI segmentation.
Gerard Sanroma,Oualid Benkarim,Gemma Piella,Karim Lekadir,N.M. Hahner,Elisenda Eixarch,Miguel Ángel González Ballester +6 more
TL;DR: Two ensembling strategies are explored, namely, stacking and cascading to combine the strengths of both families, and results show that either combination strategy outperform all of the individual methods, thus demonstrating the capability of learning systematic combinations that lead to an overall improvement.
Journal ArticleDOI
Theoretical Explorations Generate New Hypotheses About the Role of the Cartilage Endplate in Early Intervertebral Disk Degeneration
Carlos Ruiz Wills,Baptiste Foata,Miguel Ángel González Ballester,Miguel Ángel González Ballester,Jaro Karppinen,Jaro Karppinen,Jérôme Noailly +6 more
TL;DR: This theoretical study cast doubts about the paradigm that CEP calcification is needed to provoke cell starvation, and suggests an alternative path for DD whereby the early degradation of the CEP plays a key role.
Proceedings ArticleDOI
On the adequacy of principal factor analysis for the study of shape variability
Miguel Ángel González Ballester,Marius George Linguraru,Marius George Linguraru,Mauricio Reyes Aguirre,Nicholas Ayache +4 more
TL;DR: In this article, the authors propose Principal Factor Analysis (PFA) as an alternative to PCA and argue that PFA is a better suited technique for medical imaging applications, while still being a linear, efficient technique that performs dimensionality reduction.
Journal ArticleDOI
Machine Learning for Clinical Decision-Making: Challenges and Opportunities in Cardiovascular Imaging
Sergio Sanchez-Martinez,Oscar Camara,Gemma Piella,Maja Cikes,Miguel Ángel González Ballester,Marius Miron,Alfredo Vellido,Emilia Gómez,Alan G. Fraser,Bart Bijnens +9 more
TL;DR: The state-of-the-art, as well as the current clinical status and challenges associated with the two later tasks of interpretation and decision support are discussed, together with the challenges related to the learning process, the auditability/traceability, the system infrastructure and the integration within clinical processes in cardiovascular imaging.
Book ChapterDOI
A Radiomics Approach to Computer-Aided Diagnosis with Cardiac Cine-MRI.
Irem Cetin,Gerard Sanroma,Steffen E. Petersen,Sandy Napel,Oscar Camara,Miguel Ángel González Ballester,Miguel Ángel González Ballester,Karim Lekadir +7 more
TL;DR: A new approach to identify CVDs from cine-MRI by estimating large pools of radiomic features (statistical, shape and textural features) encoding relevant changes in anatomical and image characteristics due toCVDs is presented.