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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Book ChapterDOI
Computation and evaluation of medial surfaces for shape representation of abdominal organs
Sergio Vera,Debora Gil,Agnés Borràs,Xavi Sánchez,Frederic Perez,Marius George Linguraru,Miguel Ángel González Ballester +6 more
TL;DR: A standard scheme for the computation of medial manifolds that avoid degenerated medial axis segments is provided and an energy based method which performs independently of the dimension is introduced.
Journal ArticleDOI
A novel approach to multiple anatomical shape analysis: Application to fetal ventriculomegaly
Oualid Benkarim,Gemma Piella,Islem Rekik,N.M. Hahner,Elisenda Eixarch,Dinggang Shen,Dinggang Shen,Gang Li,Miguel Ángel González Ballester,Gerard Sanroma +9 more
TL;DR: This work proposes a novel approach to identify fine-grained associations between cortical folding and ventricular enlargement by leveraging the vertex-wise correlations between their growth patterns in terms of area expansion and curvature, and reveals clinically relevant and heterogeneous regional associations.
Proceedings ArticleDOI
A method for frame-by-frame us to CT registration in a joint calibration and registration framework
Matthias Peterhans,Haydar Talib,Marius George Linguraru,Martin Styner,Miguel Ángel González Ballester +4 more
TL;DR: A method is presented for achieving robust joint calibration and registration in ultrasound (US) to CT registration for computer assisted orthopedic surgery using an effectively real-time frame- by-frame registration algorithm during US image acquisition.
Book ChapterDOI
Automatic Labeling of Vascular Structures with Topological Constraints via HMM
Xingce Wang,Yue Liu,Zhongke Wu,Xiao Mou,Mingquan Zhou,Miguel Ángel González Ballester,Chong Zhang +6 more
TL;DR: Results demonstrate that the proposed graph labeling approach can achieve higher accuracy and specificity, while obtaining similar precision and recall, when comparing to the best performing state-of-the-art methods.
Book ChapterDOI
DCNN-Based Automatic Segmentation and Quantification of Aortic Thrombus Volume: Influence of the Training Approach
Karen López-Linares,Luis Kabongo,Nerea Lete,Gregory Maclair,Mario Ceresa,Ainhoa García-Familiar,Iván Macía,Miguel Ángel González Ballester +7 more
TL;DR: An automatic pipeline for thrombus volume assessment is proposed, starting from its segmentation based on a Deep Convolutional Neural Network both pre-operatively and post-operative.