Veronica Vilaplana

Positionsort descending e-mail
Associate Professor veronica.vilaplana@upc.edu
Office Phone
CN: D5-118 / ESEIAAT: TR2-102 +34 934 017 052
+34 937 398 979
Journals Books Conferences Theses Other Projects Research Demos Teaching

 

Biography

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,     ORCID: 0000-0001-6924-9961
Scopus Author ID: 23394280500,     Researcher ID: O-1726-2014,     UPC Futur 

LinkedIn,      ResearchGate

Journal Articles top

2023
I. Cumplido-Mayoral, ,, 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)
2022
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.
L. Salgueiro, Marcello, J., and Vilaplana, V., “SEG-ESRGAN: A multi-task network for super-resolution and semantic segmentation of remote sensing images”, Remote Sensing, vol. 14, no. 22, 2022.
2021
S. Abadal, Salgueiro, L., Marcello, J., and Vilaplana, V., “A Dual Network for Super-Resolution and Semantic Segmentation of Sentinel-2 imagery”, Remote Sensing, vol. 13, no. 22, p. 4547, 2021.
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Book Chapters and Bookstop

2021
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.
2018
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.
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Conference Papers top

2022
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.
M. Combalia, Podlipnik, S., Hernandez, C., García, S., Ficapal, J., Burgos, J., Vilaplana, V., and Malvehy, J., “Artificial intelligence to predict positivity of sentinel lymph node biopsy in melanoma patients”, in European Association of Dermato Oncology (EADO 2022), 2022.
I. Cumplido-Mayoral, Garcia-Prat, M., Operto, G., Falcon, C., Shekari, M., Cacciaglia, R., Mila-Aloma, M., Calvet, M. Suarez, Vilaplana, V., and Gispert, J. D., “Biological Brain Age Prediction Using Machine Learning on Structural Neuroimaging Data: Multi-Cohort Validation Against Biomarkers of Alzheimer’s Disease and Neurodegeneration”, in Alzheimer's Association International Conference, 2022.
C. Hernandez, Combalia, M., Puig, S., Malvehy, J., and Vilaplana, V., “Contrastive and attention-based multiple instance learning for the prediction of sentinel lymph node status from histopathologies of primary melanoma tumours.”, in Cancer Prevention through early detecTion (Caption) Workshop at 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2022), 2022.
O. Pina and Vilaplana, V., “Self-supervised graph representations of WSIs”, in Geometric Deep Learning in Medical Image Analysis, 2022.
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Theses top

2022
L. Salgueiro, “Super-resolution and semantic segmentation of remote sensing images using deep learning techniques”, 2022.
2019
A. Casamitjana, “Study of early stages of Alzheimer’s disease using magnetic resonance imaging”, Universitat Politècnica de Catalunya, Barcelona, 2019.
2016
C. Ventura, “Visual Object Analysis using Regions and Local Features”, 2016. (2.5 MB)
2010
V. Vilaplana, “Region-based face detection, segmentation and tracking. framework definition and application to other objects”, Universitat Politècnica de Catalunya (UPC), 2010.

Other top

2019
M. Balibrea, “Deep learning for semantic segmentation of airplane hyperspectral imaging”. 2019. Ms Thesis
L. Tarrés, “Clasificación de lesiones de piel con un ensemble de redes neuronales residuales”. 2019. Ms Thesis
T. Domenech, “Clasificación de imágenes dermatoscópicas utilizando Redes Neuronales Convolucionales e información de metadatos”. 2019. Ms Thesis
R. Casals, “Synthesis of acne images for data augmentation with generative adversarial networks”. 2019. Ms Thesis
P. Domingo, “Interpretability of Deep Learning Models”. 2019. Ms Thesis
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Projects top

AIMING: Unbiased and explainable artificial intelligence for medical imaging National Sep
2021 		Aug
2024
Implementation of personalized medicine in malignant melanoma patients aided by artificial intelligence. Other Aug
2020 		Jul
2023
A European AI On Demand Platform and Ecosystem European Jan
2019 		Dec
2021
SGR17 - Image and Video Processing Group National Jan
2017 		Sep
2021
MALEGRA - Multimodal Signal Processing and Machine Learning on Graphs National Jan
2017 		Jun
2021
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Research Areas top

Biomedical Applications Internal Jan
2012 		Dec
2024
Region-based image and video processing Internal Jan
1992 		Dec
2020
Deep learning Internal Jun
2014 		Dec
2020
Saliency prediction Internal Feb
2015 		Dec
2019
Multimedia Retrieval Internal Sep
2001 		Dec
2018

Demos and Resources top

Additional results for "Action Tube Extraction based 3D-CNN for RGB-D Action Recognition" Results May
2018
VNeAT (Voxel-wise Neuroimaging Analysis Toolbox) Software Jun
2017
Saliency Maps on Image Hierarchies Results May
2015
Automatic Keyframe Selection over TVC database Results Jun
2013

Teaching top

Acronym Title Level College
VC Computer Vision Degree in Engineering of Audiovisual Systems ESEIAAT
DLAI Deep Learning for Artificial Intelligence Master MET ETSETB TelecomBCN
PDI Digtal Image Processing Degree in Engineering of Audiovisual Systems Escola d'Enginyeria de Terrassa, EET
IPSAV Introduction to Audiovisual Signal Processing Degree in Engineering of Audiovisual Systems TelecomBCN, ETSETB
ICV Introduction to Computer Vision Master in Telecommunications Engineering (MET) ETSETB - Telecom BCN
IDL Introduction to Deep Learning BSc ETSETB TelecomBCN
IHCV M1. Introduction to Humand and Computer Vision Master in Computer Vision (MCV) UAB, UOC, UPC & UPF
CLP Pattern recognition and machine learning Degree in Telecommunications Technologies and Services Engineering Telecom BCN - ETSETB