Machine Learning for Biological and Medical Image Computing

During the last century, continuous advances in biological and medical imaging technologies gave rise to a wide variety of visual representations of the interior of living organisms (e.g. humans, animals, plants) at the organ, tissue, cellular and molecular level. Modalities such as x-ray, nuclear and molecular imaging, ultrasound, magnetic resonance imaging and scanning microscopies play a crucial role in clinical practice and basic life sciences research. The last decades saw the advent of new digital technologies which lead to a massive production of image data, inconceivable twenty years ago. Nowadays it is possible to process and understand this data thanks to the development of computational methods for the analysis of biomedical images. These methods constitute a well-established multidisciplinary field of research which lies in the intersection of several areas like computer sciences, maths, medicine and biology. We aim at developing novel machine learning methods to tackle some of the main problems in the field of biological and medical image analysis, including image registration, segmentation and classification, with particular focus on deep learning models. Our goal is to address fundamental machine learning problems such as domain adaptation, algorithmic fairness, learning with limited data and non-regular structures which arise in the context of image analysis for biology and medicine.

Team members

Enzo Ferrante
Diego Milone
Rodrigo Echeveste
Lucas Mansilla
Franco Matzkin
Nicolas Gaggion
Agostina Larrazabal
Nicolas Nieto
Victoria Peterson

Selected publications

A. Larrazabal, N. Nieto, V. Peterson, D. H. Milone, E. Ferrante
Proceedings of the National Academy of Sciences – 2020
L. Mansilla, D. H. Milone, E. Ferrante
Neural Networks, Volume 124, page 269–279 – 2020
A. Larrazabal, C. E. Martínez, B. Glocker, E. Ferrante
IEEE Transactions on Medical Imaging – 2020
F. Matzkin, V. F. J. Newcombe, S. Stevenson, A. Khetani, T. Newman, R. Digby, A. Stevens, B. Glocker, E. Ferrante
Medical Image Computing and Computer Assisted Intervention — MICCAI 2020 – 2020
Publications in 2019
E. Fernández, E. Ferrante
Master thesis from Facultad de Ciencias Exactas y Naturales – Universidad de Buenos Aires – 2019
A. Larrazabal, C. E. Martínez, E. Ferrante
MICCAI 2019: International Conference on Medical Image Computing and Computer-Assisted Intervention – 2019
F. Matzkin, E. Ferrante
Master thesis from Facultad de Ingeniería y Ciencias Hídricas – Universidad Nacional del Litoral – 2019
J. Bhalodiya, A. Palit, E. Ferrante, M. K. Tiwari, S. K. Bhudia, T. N. Arvanitis, M. A. Williams
Scientific reports, Volume 9, Number 1, page 1–13 – 2019
N. Roulet, D. Fernandez Slezak, E. Ferrante
Proceedings of The 2nd International Conference on Medical Imaging with Deep Learning, Volume 102, page 401-413 – 08–10 Jul 2019
M. Monteiro, Kamnitsas K., E. Ferrante, et al.
MICCAI Brain Lesion Workshop – 2019
J. Cerrolaza, M. Sinclair, Y. Li, A. Gómez, E. Ferrante, J. Matthew, C. Gupta, C. Knight, D. Rueckert
Biomedical Imaging (ISBI 2018), 2018 IEEE 15th International Symposium on, page 564–567 – 2018
S. Parisot, S. I. Ktena, E. Ferrante, M. Lee, R. Guerrero, B. Glocker, D. Rueckert
Medical Image Analysis – 2018
D. Stoyanov, Z. Taylor, E. Ferrante, A. Dalca, A. Martel, L. Maier-Hein, S. Parisot, A. Sotiras, B. Papiez, M. Sabuncu, L. Shen
Springer – 2018
A. Debus, E. Ferrante
Statistical Atlases and Computational Modeling of the Heart (STACOM 2018) – 2018
E. Ferrante, O. Oktay, B. Glocker, D. H. Milone
International Workshop on Machine Learning in Medical Imaging, page 294–302 – 2018
N. Roulet, D. Fernandez Slezak, E. Ferrante
Master thesis from Facultad de Ciencias Exactas y Naturales – Universidad de Buenos Aires – 2018
L. Mansilla, E. Ferrante
XXIV Congreso Argentino de Ciencias de la Computación (La Plata, 2018). – 2018
E. Ferrante, P. Dokania, R. Marini, P. Nikos
IEEE journal of biomedical and health informatics – 2018
Publications in 2017
O. Oktay, E. Ferrante, K. Kamnitsas, M. Heinrich, W. Bai, J. Caballero, R. Guerrero, S. Cook, A. Marvao, T. Dawes, D. O Regan, B. Kainz, B. Glocker, D. Rueckert
IEEE Transactions on Medical Imaging – 2017
E. Ferrante, P. Dokania, R. Marini, N. Paragios
8th International Workshop on Machine Learning in Medical Imaging – 2017