|
Author |
Title |
Year |
Publication |
Volume |
Pages |
Links |
|
David Roche |
A Statistical Framework for Terminating Evolutionary Algorithms at their Steady State |
2015 |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
|
|
|
|
Patricia Marquez |
A Confidence Framework for the Assessment of Optical Flow Performance |
2015 |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
|
|
|
|
Sergio Vera |
Anatomic Registration based on Medial Axis Parametrizations |
2015 |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
|
|
|
|
Debora Gil; F. Javier Sanchez; Gloria Fernandez Esparrach; Jorge Bernal |
3D Stable Spatio-temporal Polyp Localization in Colonoscopy Videos |
2015 |
Computer-Assisted and Robotic Endoscopy. Revised selected papers of Second International Workshop, CARE 2015, Held in Conjunction with MICCAI 2015 |
9515 |
140-152 |
|
|
H. Martin ; Jens Fagertun; Sergio Vera; Debora Gil |
Medial structure generation for registration of anatomical structures |
2017 |
Skeletonization, Theory, Methods and Applications |
11 |
|
|
|
Antonio Esteban Lansaque |
An Endoscopic Navigation System for Lung Cancer Biopsy |
2019 |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
|
|
|
|
Debora Gil; Oriol Ramos Terrades; Raquel Perez |
Topological Radiomics (TOPiomics): Early Detection of Genetic Abnormalities in Cancer Treatment Evolution |
2021 |
Extended Abstracts GEOMVAP 2019, Trends in Mathematics 15 |
15 |
89–93 |
|
|
Jose Elias Yauri |
Deep Learning Based Data Fusion Approaches for the Assessment of Cognitive States on EEG Signals |
2023 |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
|
|
|
|
David Roche; Debora Gil; Jesus Giraldo |
Mathematical modeling of G protein-coupled receptor function: What can we learn from empirical and mechanistic models? |
2014 |
G Protein-Coupled Receptors – Modeling and Simulation Advances in Experimental Medicine and Biology |
796 |
159-181 |
|
|
Debora Gil; Petia Radeva |
Curvature Vector Flow to Assure Convergent Deformable Models for Shape Modelling |
2003 |
Energy Minimization Methods In Computer Vision And Pattern Recognition |
2683 |
357-372 |
|