Veronica Vilaplana


Veronica Vilaplana holds a MSc degree in Mathematics and a MSc degree in Computer Sciences from the Universidad de Buenos Aires (Argentina), and a PhD in Signal Theory and Communications from the Universitat Politècnica de Catalunya (UPC). Since 2002 she is associate professor at the Department of Signal Theory and Communications (UPC). Her current research interests focus on deep learning and other machine learning models for biomedical and remote sensing applications. 

Scientific IDs:

Google Scholar,     ORCID0000-0001-6924-9961
Scopus Author ID: 23394280500,     Researcher ID: O-1726-2014,     UPC Futur 

LinkedIn,      ResearchGate

Journal Articles top

In Press
C. Pachón-García, Hernandez, C., Delicado, P., and Vilaplana, V., SurvLIMEpy: A Python package implementing SurvLIME, Expert Systems With Applications, In Press.
I. Cumplido-Mayoral, García-Prat, M., Operto, G., Falcon, C., Shekari, M., Cacciaglia, R., Mila-Aloma, M., Lorenzini, L., Minguillon, C., Molinuevo, J. Luis, Suarez-Calvet, M., Vilaplana, V., and Gispert, J. Domingo, Biological Brain Age Prediction Using Machine Learning on Structural Neuroimaging Data: Multi-Cohort Validation Against Biomarkers of Alzheimer’s Disease and Neurodegeneration stratified by sex, eLife, vol. 12, 2023.
J. Gené-Mola, Ferrer-Ferrer, M., Gregorio, E., Blok, P. M., Hemming, J., Morros, J. R., Rosell-Polo, J. R., Vilaplana, V., and Ruiz-Hidalgo, J., Looking behind occlusions: A study on amodal segmentation for robust on-tree apple fruit size estimation, Computers and Electronics in Agriculture, vol. 209, 2023. (9.02 MB)
M. Ferrer-Ferrer, Ruiz-Hidalgo, J., Gregorio, E., Vilaplana, V., Morros, J. R., and Gené-Mola, J., Simultaneous Fruit Detection and Size Estimation Using Multitask Deep Neural Networks  , Biosystems Engineering, vol. 233, pp. 63-75, 2023. (10.36 MB)
R. Metha, Filos, A., Baid, U., Mora, L., Vilaplana, V., Davatzikos, C., Menze, B., Bakas, S., Gal, Y., and Arbel, T., QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation--Analysis of Ranking Metrics and Benchmarking Results, Journal of Machine Learning for Biomedical Imaging, 2022.

Book Chapters and Bookstop

L. Mora and Vilaplana, V., MRI brain tumor segmentation and uncertainty estimation using 3D-UNet architectures, in Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2020, vol. 12658, Springer International Publishing, 2021, pp. 376-390.
M. Combalia and Vilaplana, V., Monte-Carlo Sampling Applied to Multiple Instance Learning for Histological Image Classification, in Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, Springer International Publishing, 2018, pp. 274-281.
M. Górriz, Aparicio, A., Raventós, B., Vilaplana, V., Sayrol, E., and López-Codina, D., Leishmaniasis Parasite Segmentation and Classification Using Deep Learning, in Articulated Motion and Deformable Objects, vol. 10945, Springer International Publishing, 2018, pp. 53-62.
A. Casamitjana, Vilaplana, V., Petrone, P., Molinuevo, J. Luis, and Gispert, J. D., Shared Latent Structures Between Imaging Features and Biomarkers in Early Stages of Alzheimer’s Disease, in PRedictive Intelligence in MEdicine, vol. 11121, Springer International Publishing, 2018, pp. 60-67.
A. Casamitjana, Catà, M., Sánchez, I., Combalia, M., and Vilaplana, V., Cascaded V-Net Using ROI Masks for Brain Tumor Segmentation, in Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2017, Crimi A., Bakas S., Kuijf H., Menze B., Reyes M. (eds)., vol. 10670, Cham: Springer, 2018, pp. 381-391.

Conference Papers top

O. Pina and Vilaplana, V., Layer-wise self-supervised learning on graphs, in KDD 2023 Workshop on Deep Learning on Graphs: Methods and Applications (DLG-KDD 2023), Long Beach, USA, Submitted.
I. Cumplido-Mayoral, Mila-Aloma, M., Falcon, C., Cacciaglia, R., Minguillon, C., Fauria, K., Molinuevo, J. Luis, Vilaplana, V., and Gispert, J. D., Brain-age prediction and its associations with glial and synaptic CSF markers, in Alzheimer's Association International Conference, Amsterdam, Netherlands, 2023.
I. Cumplido-Mayoral, Brugulat-Serrat, A., Sánchez-Benavides, G., González-Escalante, A., Anastasi, F., Mila-Aloma, M., Falcon, C., Shekari, M., Cacciaglia, R., Minguillon, C., Vilaplana, V., and Gispert, J. D., Brain-age mediates the association between modifiable risk factors and cognitive decline early in the AD continuum, in Alzheimer’s Association International Conference (AAIC), Amsterdam, Netherlands, 2023.
C. Hernandez, Pachón-García, C., Delicado, P., and Vilaplana, V., Interpreting Machine Learning models for Survival Analysis: A study of Cutaneous Melanoma using the SEER Database, in XAI-Healthcare 2023 Workshop at 21st International Conference of Artificial Intelligence in Medicine (AIME 2023), Portoroz, Slovenia, 2023.
C. Hernandez, Vilaplana, V., Combalia, M., García, S., Podlipnik, S., Burgos, J., Puig, S., and Malvehy, J., Sentinel lymph node status prediction with self-attention neural networks using histologies of primary melanoma tumours, in European Association of Dermato Oncology (EADO 2022), 2022.

Research Areas top

Biomedical Applications Internal Jan
Region-based image and video processing Internal Jan
Deep learning Internal Jun
Saliency prediction Internal Feb
Multimedia Retrieval Internal Sep