Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018 | 2061 | 2018 |
A new quality metric for image fusion G Piella, H Heijmans Proceedings 2003 international conference on image processing (Cat. No …, 2003 | 1329 | 2003 |
A general framework for multiresolution image fusion: from pixels to regions G Piella Information Fusion 4 (4), 259--280, 2003 | 1132 | 2003 |
Machine learning‐based phenogrouping in heart failure to identify responders to cardiac resynchronization therapy M Cikes, S Sanchez‐Martinez, B Claggett, N Duchateau, G Piella, ... European journal of heart failure 21 (1), 74-85, 2019 | 241 | 2019 |
Adaptive Lifting Schemes with Perfect Reconstruction G Piella, H Heijmans IEEE Transactions on Signal Processing, 50: 50, 1620—1630, 2002 | 197 | 2002 |
Image fusion for enhanced visualization: A variational approach G Piella International journal of computer vision 83, 1-11, 2009 | 183 | 2009 |
Temporal diffeomorphic free-form deformation: Application to motion and strain estimation from 3D echocardiography M De Craene, G Piella, O Camara, N Duchateau, E Silva, A Doltra, ... Medical image analysis 16 (2), 427-450, 2012 | 181 | 2012 |
A region-based multiresolution image fusion algorithm G Piella Proceedings of the Fifth International Conference on Information Fusion …, 2002 | 154 | 2002 |
Machine learning analysis of left ventricular function to characterize heart failure with preserved ejection fraction S Sanchez-Martinez, N Duchateau, T Erdei, G Kunszt, S Aakhus, ... Circulation: cardiovascular imaging 11 (4), e007138, 2018 | 132 | 2018 |
Towards content-oriented patent document processing L Wanner, R Baeza-Yates, S Brügmann, J Codina, B Diallo, E Escorsa, ... World Patent Information 30 (1), 21-33, 2008 | 122 | 2008 |
Building nonredundant adaptive wavelets by update lifting HJMA Heijmans, B Pesquet-Popescu, G Piella Appl. Comput. Harmon. Anal 18, 352-81, 2005 | 107 | 2005 |
Integration of convolutional neural networks for pulmonary nodule malignancy assessment in a lung cancer classification pipeline I Bonavita, X Rafael-Palou, M Ceresa, G Piella, V Ribas, MAG Ballester Computer methods and programs in biomedicine 185, 105172, 2020 | 96 | 2020 |
Segmentation and classification in MRI and US fetal imaging: recent trends and future prospects J Torrents-Barrena, G Piella, N Masoller, E Gratacós, E Eixarch, M Ceresa, ... Medical Image Analysis 51, 61-88, 2019 | 93 | 2019 |
A spatiotemporal statistical atlas of motion for the quantification of abnormal myocardial tissue velocities N Duchateau, M De Craene, G Piella, E Silva, A Doltra, M Sitges, ... Medical image analysis 15 (3), 316-328, 2011 | 89 | 2011 |
Memory-aware curriculum federated learning for breast cancer classification A Jiménez-Sánchez, M Tardy, MAG Ballester, D Mateus, G Piella Computer Methods and Programs in Biomedicine 229, 107318, 2023 | 86 | 2023 |
A survey on machine and statistical learning for longitudinal analysis of neuroimaging data in Alzheimer’s disease G Martí-Juan, G Sanroma-Guell, G Piella Computer methods and programs in biomedicine 189, 105348, 2020 | 83 | 2020 |
Adaptive update lifting with a decision rule based on derivative filters G Piella, B Pesquet-Popescu, HJMA Heijmans IEEE Signal Processing Letters 9 (10), 329--332, 2002 | 82 | 2002 |
3D Strain Assessment in Ultrasound (Straus): A Synthetic Comparison of Five Tracking Methodologies M De Craene, S Marchesseau, B Heyde, H Gao, M Alessandrini, ... IEEE Transactions on Medical Imaging 32 (9), 1632-46, 2013 | 81 | 2013 |
Characterization of myocardial motion patterns by unsupervised multiple kernel learning S Sanchez-Martinez, N Duchateau, T Erdei, AG Fraser, BH Bijnens, ... Medical image analysis 35, 70-82, 2017 | 77 | 2017 |
Survey on 3D face reconstruction from uncalibrated images A Morales, G Piella, FM Sukno Computer Science Review 40, 100400, 2021 | 62 | 2021 |