Enzo Ferrante

CONICET Research Scientist

News!

- 2022, January: I was invited to moderate the presentation given by Lelia Marie Hampton at the the AI for Good talk series about "AI enabled public health from a marginalized perspective".
- 2021, December: On December 6th I gave a seminar at the AI for Good talk series organized by the International Telecomunications Union (ITU@United Nations) about "Fairness of machine learning classifiers in medical image analysis". Video available in the Talks tab.
- 2021, December: Our work at ARPH.AI on de-binarization of gender identity on the Argentina’s Electronic Health Record System was featured by the Global South AI for COVID program
- 2021, November: I was invited to give a seminar about "Gender bias in X-ray classifiers for computer-assisted diagnosis" at the Responsible AI Seminar organized by the Danmarks Tekniske Universitet (DTU). Video available in the Talks tab.
- 2021, July: Our paper Domain Generalization via Gradient Surgery was accepted for publication at ICCV 2021..
- 2021, July: I received the Honorable Mention Reviewer Award for MICCAI 2021..
- 2021, July: I joined the A. Martinos Center for Biomedical Imaging (Massachusetts General Hospital - Harvard Medical School) in Boston, as a Fulbright Visitng Researcher during the summer! I'll be working with Juan Eugenio Iglesias, Adrian Dalca and Burce Fischl. If you are in the Boston area and want to meet, just drop me a message! .
- 2021, June: Our work "HybridGNet: Hybrid graph convolutional neural networks for landmark-based anatomical segmentation" was accepted at MICCAI 2021! Joint work with Nicolás Gaggion, Lucas Mansilla and Diego Milone..
- 2021, May: I received the Outstanding Reveiwer Award for CVPR 2021..
- 2021, May: Our work "Orthogonal Ensemble Networks for Biomedical Image Segmentation" was (early) accepted at MICCAI 2021! Joint work with Agostina Larrazabal, Cesar Martinez and Jose Doltz..
- 2021, May: I was invited as keynote speaker to Khipu 2021, to talk about self-supervised learning in biomedical image analysis, toghether with Yann Lecun and Sandra Avila. The talk is available here..
- 2021, January: Nicolás Nieto was awarded the Junior Research Parasite Award for our work "Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis", published last year in PNAS.
- 2020, December: I was awarded the Mercosur Science and Technology Award on the topic "Artificial Intelligence".
- 2020, November: We received an International Exchanges Grant from the Royal Society (UK) to support our project on Imaging Genetics with Alex Frangi and Rodrigo Bonazolla (University of Leeds).
- 2020, November: Computer Vision News featured an interview to Franco Matzkin, one of my PhD students, about our MICCAI and Autoimplant Challenge papers on skull reconstruction!
- 2020, October: I received the Young Investigator Award from the National Academy of Exact, Physical and Natural Sciences of Argentina
- 2020, October: Our work "Cranial Implant Design via Virtual Craniectomy with Shape Priors" (with F Matzkin, V Newcombe & B Glocker) received a Best Paper Award from the MICCAI Autoimplant Workshop 2020.
- 2020, October:I co-organized the 3rd International Workshop on Graphs in Biomedical Image Analysis (GRAIL) at MICCAI 2020.
- 2020, October: Julian Palladino presented our work "Unsupervised Domain Adaptation via CycleGAN for White Matter Hyperintensity Segmentation in Multicenter MR Images" at SIPAIM 2020, jointly organized with MICCAI.
- 2021, September: I was invited to give a talk (see the recorded talk here) at the seminar organized by the Center for Imaging Science (CIS) and the Mathematical Institute for Data Science (MINDS), at Johns Hopkins University, about our work on anatomically plausible medical image processing.
- 2020, August: I was invited to present our work "Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis" recently published in PNAS at the Stanford AIMI Journal Club. Video available in the Talks tab.
- 2020, May: Our article "Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis" was just published in PNAS and featured by STAT News.
- 2020, May: I added this news section to my website! .

About me

I hold a permenent position as CONICET faculty researcher in Argentina, leading a research line on machine learning methods for biological and medical image analysis at the Research institute for signals, systems and computational intelligence (CONICET / Universidad Nacional del Litoral) in Santa Fe, Argentina. I'm also a professor at Universidad Torcuato Di Tella and Universidad de San Andrés, in Buenos Aires, Argentina. In 2012 I received my Systems Engineering Degree from UNICEN University, Tandil, Argentina. In May 2016, I defended my PhD thesis in Computer Sciences, at the Université Paris-Saclay (CentraleSupeléc / INRIA) in France (Paris) where I worked on deformable registration of multimodal medical images, using graphical models and discrete optimization techniques, under the supervision of Prof. Nikos Paragios. After that, until August 2017, I was a postdoc research associate at Imperial College London (BioMedIA lab), under the supervision of Prof. Ben Glocker working on deep learning and brain image segmentation.

I have also worked at several research institutes around the world. In 2021, I received a Fulbright Fellowship to visit the A. Martinos Center for Biomedical Imaging (Massachusetts General Hospital - Harvard Medical School) in Boston. In 2014, as PhD intern I spend 3 months working on shape understanding for the Computer Vision and Geometry Lab at Stanford University, California, USA. During 2010, I was an intern at STEEP Team (INRIA Grenoble, France) working on transport/land-use mathematical modeling.

Contact email: eferrante (at) sinc (dot) unl (dot) edu (dot) ar || ferrante.enzo (at) gmail (dot) com

Colleagues, friends, master and PhD students with whom I work at the Research Institute for Signals, Systems and Computational Intelligence in Santa Fe city, Argentina.

Video presentations and talks

AI for Good Seminar

November, 2021: Invited talk about "Fairness of machine learning classifiers in medical image analysis" at the AI for Good series organized by International Telecommunication Union.

Responsible AI Seminar @ Technical University of Denmark

November, 2021: Invited talk at the Responsible AI Seminar organized by the Technical University of Denmark about fairness in machine learning for medical image analysis.

Khipu 2021

May, 2021: Invited talk at Khipu 2021 about self-supervised learning in biomedical image analysis, toghether with Yann Lecun and Sandra Avila.

Stanford AIMI Journal Club

August, 2020: Invited talk about our paper "Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis"

MINDS & CIS Seminar, Johns Hopkins University

September, 2020: Invited talk at the seminar organized by the Center for Imaging Science (CIS) and the Mathematical Institute for Data Science (MINDS), Johns Hopkins University. I presented our research line on anatomically plausible medical image segmentation, registration and reconstruction, featuring works from Lucas Mansilla, Agostina Larrazabal and Franco Matzkin.

Giambiagi Winter School 2020

August, 2020: I gave an introductory course to convolutional neural networks at the Giambiagi Winter School, organized by the Physics Department of Universidad de Buenoa Aires, Argentina. Talk in spanish.

Class 1:

Class 2:

Khipu 2019

November, 2019: I was invited as a plenary speaker to the 1st Latin American meeting on Artificial Intelligence, Khipu 2019, organized in Uruguay. My talk was an introduction to convolutional neural networks.

Publications

I'm including a list of selected publications, for a full list see my Google Scholar Profile. If you have troubles to access them, please email me.

Domain Generalization via Gradient Surgery
[ICCV 2021 (ArXiv Version)]
L Mansilla, R Echeveste, DH Milone, E Ferrante
ICCV 2021

Hybrid graph convolutional neural networks for landmark-based anatomical segmentation
[MICCAI 2021 (ArXiv version)]
N Gaggion, L Mansilla, DH Milone, E Ferrante
MICCAI 2021

Orthogonal Ensemble Networks for Biomedical Image Segmentation
[MICCAI 2021 (ArXiv version)]
A Larrazabal, C Martinez, J Dolz, E Ferrante
MICCAI 2021

ChronoRoot: High-throughput phenotyping by deep segmentation networks reveals novel temporal parameters of plant root system architecture
[GigaScience]
N Gaggion, L Mansilla, DH Milone, E Ferrante
GigaScience (2021) https://doi.org/10.1093/gigascience/giab052

Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis
[PNAS]
AJ Larrazabal, N Nieto, V Peterson, DH Milone, E Ferrante
Proceedings of the Natural Academy of Sciences (PNAS, 2020)

Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning: an algorithm development and multicentre validation study
[The Lancet DH]
M Monteiro, VFJ Newcombe, F Mathieu, K Adatia, K Kamnitsas, E Ferrante, T Das, D Whitehouse, D Rueckert, DK Menon, B Glocker
The Lancet Digitial Health (The Lancet, Elsevier, 2020)

Learning deformable registration of medical images with anatomical constraints
[ArXiV] [Neural Networks (Elsevier)]
Mansilla L, Milone D, Ferrante E
Neural Networks (Elsevier, 2020)

Self-supervised Skull Reconstruction in Brain CT Images with Decompressive Craniectomy
[ArXiv]
F Matzkin, V Newcombe, S Stevenson, A Khetani, T Newman, R Digby, A Stevens, B Glocker, E Ferrante
MICCAI 2020

Cranial Implant Design via Virtual Craniectomy with Shape Priors
[ArXiv]
F Matzkin, V Newcombe, B Glocker, E Ferrante
AutoImplant Challege 2020 (MICCAI 2020)
Received the Best Paper Award at AutoImplant Challenge.

Unsupervised Domain Adaptation via CycleGAN for White Matter Hyperintensity Segmentation in Multicenter MR Images
[ArXiv]
JA Palladino, DF Slezak, E Ferrante
SIPAIM 2020 (Jointly organized with MICCAI 2020)

Anatomical Priors for Image Segmentation via Post-Processing with Denoising Autoencoders
[ArXiV] [Springer LNCS]
Larrazabal A, Martinez C, Ferrante E
MICCAI 2019

Joint Learning of Brain Lesion and Anatomy Segmentation from Heterogeneous Dataset
[PMLR] [Open Reviews] [ArXiv Version]
Roulet N, Fernandes Slezak D, Ferrante E
International Conference on Medical Imaging with Deep Learning (MIDL 2019)

TBI Lesion Segmentation in Head CT: Impact of Preprocessing and Data Augmentation
[ArXiv][Springer LNCS]
M Monteiro, K Kamnitsas, Ferrante E, F Mathieu, S McDonagh, S Cook, S Stevenson, T Das, A Khetani, T Newman, F Zeiler, R Digby, J P Coles, D Rueckert, DK Menon, VFJ Newcombe, B Glocker
BrainLess Workshop (MICCAI, 2019)

Hierarchical Template Matching for 3D Myocardial Tracking and Cardiac Strain Estimation
[Nature Scientific Reports]
JM Bhalodiya, A Palit, Ferrante E, MK Tiwari, SK Bhudia, TN Arvanitis, MA Williams
Nature Scientific Reports (Nature Sci Rep, 2019)

Weakly-Supervised Learning of Metric Aggregations for Deformable Image Registration
[ArXiv Version, IEEE Version]
Ferrante E, K Dokania P, Marini Silva R, Paragios N
IEEE Journal of Biomedical and Health Informatics (2019, IEEE)

On the Adaptability of Unsupervised CNN-Based Deformable Image Registration to Unseen Image Domains
[ReserachGate Version]
Ferrante E, Oktay O, Glocker B, Milone D
International Conference on Machine Learning in Medical Imaging (MLMI 2018, MICCAI 2018)

Left ventricle quantification through spatio-temporal CNNs
[ArXiv Version]
A Debus, Ferrante E
Statistical Atlases and Computational Modelling of the Heart (STACOM 2018, MICCAI 2018)

Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer’s disease
[Github Project and Code]
Parisot S, Ktena SI, Ferrante E, Lee M, Guerrerro R, Glocker B, Rueckert D
Medical Image Analysis (2018, IEEE)

Graph Based Slice-to-Volume Deformable Registration
[ResearchGate Open Manuscript, Springer IJCV Publication]
Ferrante E, Paragios N
International Journal of Computer Vision (2018, Springer IJCV)

Metric learning with spectral graph convolutions on brain connectivity networks
[Github Project and Code]
Ktena SI, Parisot S, Ferrante E, Rajchl M, Lee M, Glocker B,Rueckert D
Neuroimage (2017, Elsevier)

Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation
Method that achieved the 1st position in the competition (out of +50 participants). See press article in [English] [Spanish]
[Arxiv Open Manuscript]
Kamnitsas K, Bai W*, Ferrante E*, McDonagh S*, Sinclair M*, Pawlowski N, Rajchl M, Lee M, Kainz B, Rueckert D, Glocker B
BRATS - The Multimodal Brain Tumor Segmentation Challenge (MICCAI 2017)

Deformable Registration through Learning of Context-Specific Metric Aggregation
[Arxiv Open Manuscript, Springer LNCS Publication]
Ferrante E, Dokania KP, Marini R, Paragios N
Machine Learning in Medical Imaging. MLMI (MICCAI 2017)

Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation
Oktay O, Ferrante E, Kamnitsas K, Heinrich M, Bai W, Caballero J, Guerrero R, Cook S, de Marvao A, O'Regan A, Kainz B, Glocker B, Rueckert D
In Press. IEEE Transactions on Medical Imaging (2017, IEEE TMI)

Slice-to-volume medical image registration: a survey
[ArXiv Manuscript, MedIA Publication]
Ferrante E, Paragios N
Medical Image Analysis (2017, Elsevier MedIA)

Spectral Graph Convolutions for Population-based Disease Prediction
[Github Project and Code]
Parisot S, Ktena SI, Ferrante E, Lee M, Guerrerro R, Glocker B, Rueckert D
MICCAI 2017

Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks
[Github Project and Code]
Ktena SI, Parisot S, Ferrante E, Rajchl M, Lee M, Glocker B,Rueckert D
MICCAI 2017

DeepMedic for Brain Tumor Segmentation
[Project website (code and downloads)]
Kamnitsas K, Ferrante E, Parisot S, Ledig C, Nori A, Criminisi A, Rueckert D, Glocker B
BRATS - The Multimodal Brain Tumor Segmentation Challenge (MICCAI 2016)

Rigid Slice-To-Volume Medical Image Registration through Markov Random Fields
[Project website (code and downloads)]
Porchetto R, Stramana F, Paragios N, Ferrante E
Bayesian and Graphical Models for Biomedical Imaging Workshop (MICCAI 2016)

(Hyper)-Graphical Models in Biomedical Image Analysis
Paragios N, Ferrante E, Glocker B, Komodakis N, Parisot S, Zacharaki E
Medical Image Analysis (2016, Elsevier MedIA)

Prior-based Coregistration and Cosegmentation
[ResearchGate] [ArXiv] [Supplementary Material]
Shakeri M*, Ferrante E*, Tskogkas S, Lippe S, Kadoury S, Kokkinos I,
Paragios N (* joint first author)
MICCAI 2016

Sub cortical brain structure segmentation using F-CNN's
[ArXiv][Project website (code and downloads)]
*Shakeri M, *Tsogkas S, Ferrante E, Lippe S, Kadoury S, Paragios N, Kokkinos I
ISBI 2016, Czech Republic

Implicit Planar and In-Plane Deformable Mapping in Medical Images Through High Order Graphs
Ferrante E, Fecamp V, Paragios N
ISBI 2015 (Oral presentation), USA

Slice-to-Volume Deformable Registration: Efficient one shot consensus between plane selection and in-plane deformation Download final draft in PDF
Ferrante E, Fecamp V, Paragios N
International Journal for Computer Assisted Radiology and Surgery (2015, Springer IJCARS)

Non-rigid 2D-3D Medical Image Registration using Markov Random Fields
Ferrante E, Fecamp V, Paragios N
MICCAI 2013, Japon

Extracción de objetos en imágenes médicas tridimensionales basada en características texturales
Manterola H L, Orlando J I, Ferrante E, del Fresno M
Proceedings of CAIS 2013, 42nd JAIIO. Argentina

Optimización de Atlas de Textura Utilizando Compactación de Polígonos por Simulación Física
Roo J S, D’Amato J P, Ferrante E
Proceedings of WAVi 2012. Argentina

Un enfoque híbrido para la segmentación de tumores en MRI cerebrales
Orlando J I, Ferrante E, Manterola H L, del Fresno M.
Proceedings of CAIS 2012, 41st JAIIO. Argentina.

Plataforma para el desarrollo de aplicaciones interactivas y Videojuegos SATVD-T
Ferrante, E, García Bauza C, Segundo R M C, Vénere M.
Proceedings of WAVi 2011. Argentina.

Detección y reconstrucción de geometrías a partir de imágenes de resonancia magnética para seguimiento de tumores
Ferrante E, del Fresno M, D’Amato J, Vénere M.
Mecánica Computacional, Vol XXX.

Segmentación de MRI aplicada al análisis de la evolución de tumores en series temporalmente espaciadas
Ferrante E del Fresno M, Escobar P, Massa, J.
Proceedings of CAIS 2011, 40th JAIIO. Argentina

Computational Logic

Educational Software for First Order Logic Semantics in Introductory Logic Courses
Mauco V, Ferrante E
Presented at ISECON 2013, USA. Published at Information Systems Education Journal.

FOLST: A Didactic Tool to Support First Order Logic Semantics Learning
Mauco V, Maggiori E, Gervasoni L, Ferrante E, Felice L.
Proceedings of ICFCE 2012, China
[Project website]

Clausula: A Didactic Tool to Teach First Order Logic
Mauco V, Ferrante E
Proceedings of ISECON 2009, USA
[Project Website]

Clausula: Herramienta Didáctica para la Enseñanza de Lógica de Predicados de Primer Orden
Ferrante E
Proceedings of JAIIO EST 2009, Argentina

Books

Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis
Editors: CH Sudre, H Fehri, T Arbel, CF. Baumgartner, A Dalca, R Tanno, K Van Leemput, WM Wells, A Sotiras, B Papiez, E Ferrante, S Parisot, AV. Dalca
Part of the Lectures Notes in Computer Sciences book series (Vol 12443)
Springer, 2020
Graphs in Biomedical Image Analysis and Integrating Medical Imaging and Non-Imaging Modalities
Editors: D Stoyanov, Z Taylor, E Ferrante, AV. Dalca et al.
Part of the Lectures Notes in Computer Sciences book series (Vol 11044)
Springer, 2018

Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics
Editors: J Cardoso, T Arbel, E Ferrante, X Pennec, A Dalca, S Parisot, S Joshi, N Batmanghelich, A Sotiras, M Nielsen, M Sabuncu, T Fletcher, L Shen, S Durrleman, S Sommer
Part of the Lectures Notes in Computer Sciences book series (Vol 10551)
Springer, 2017

PhD Thesis

Graph-based deformable registration: slice-to-volume mapping and context specific methods
Ferrante E
Director: Nikos Paragios.
2016

Engineering Thesis

Tesis de Grado: Segmentación y reconstrucción eficiente de mallas para seguimiento de tumores utilizando GPU.
Ferrante E
Director: Del Fresno, M. Co-Director: D'Amato J P.
Tesis de Grado presentada para obtener el titulo de Ingeniero de Sistemas en la Facultad de Ciencias Exactas de la Universidad Nacional del Centro de la Provincia de Buenos Aires. 2012

Program Comittee Member / Organizer

- MICCAI 2018, 2020 (International Conference on Medical Image Computing and Computer Assisted Intervention): Member of the program committee (Area Chair)
- MIDL 2020 (International Conference on Medical Imaging with Deep Learning): Member of the program committee (Area Chair)
- DART 2019, 2020 (Workshop on Domain Adaptation and Representation Transfer @ MICCAI): Member of the Program Committee
- GRAIL 2017, 2018, 2020 @ MICCAI (Graphs in Biomedical Image Processing Workshop): Co-organizer
- LDD 2017 @ NIPS, 2019 @ ICLR (Learning with limited labeled data: weak supervision and beyond): Member of the Program Committee
- AGRANDA 2019Simposio Argentino de Ciencia de Datos y GRANdes DAtos: General Chair
- MedNIPS 2018, 2019 (Medical Imaging meet NIPS Workshop @ NIPS 2018): Member of the program committee

Reviewing

- Frontiers in Neuroscience
- IEEE, Transactions on Medical Imaging (TMI)
- Elsevier, NeuroImage
- Elsevier, Medical Image Analysis (MedIA)
- Elsevier, Computers in Biology and Medicine (CBM)
- Elsevier, Computers Vision and Image Understanding (CVIU)
- Elsevier, Computerized Medical Imaging and Graphics (CMIG)
- Springer, International Journal for Computer Assisted Radiology and Surgery (IJCARS)
- MICCAI 2016, 2017, 2019 (International Conference on Medical Image Computing and Computer Assisted Intervention)
- SIPAIM 2016 (International Symposium on Medical Information Processing and Analysis)
- CIARP 2015 (Iberoamerican Congress on Pattern Recognition)
- ICVGIP 2014 (Indian Conference on Computer Vision, Graphics and Image Processing)

Teaching

Courses

February 2022: Visiting Professor in charge of “Deep learning for medical image analysis“
Universidad de la República, Uruguay
2021 - To date: Professor in charge of “Introduction to Neural Networks“
Universidad de San Andres, Argentina
2020 - To date: Professor in charge of “Introduction to Deep learning“
Universidad Torcuato di Tella, Argentina
2018-To date: Lecturer in “Digital Image Processing“
Universidad Nacional del Litoral, Argentina
November 2018: Visiting Professor in charge of “Deep learning for medical image analysis“
Departamento de Computación, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Argentina
2013-2014: Teaching Assistant in “IS1210AB – Algorithmique – Programmation“
École Centrale Paris, France
2012-2014: Teaching Assistant in “MA2818JA – Introduction to computer and artificial vision“
École Centrale Paris, France
2012-2013: Teaching Assistant in “MA2500FA – Signal Processing”
École Centrale Paris, France
2011 – 2012: Teaching Assistantin “Analysis and Design of Algorithms I and II“
Universidad Nacional del Centro de la Provincia de Buenos Aires (UNICEN), Argentina
2009 – 2012: Teaching Assistant in “Computer Science II” (Computational Logic)
Universidad Nacional del Centro de la Provincia de Buenos Aires (UNICEN), Argentina

Advising

Engineering Degree Thesis. Métodos discretos para la registración de imágenes médicas: un algoritmo para el caso slice-to-volume.
R. Porchetto, F. Stramana.
Director: J. M. Massa. Co-director: E. Ferrante.
Universidad Nacional del Centro de la Provincia de Buenos Aires (UNICEN), Argentina (2016)
Engineering Degree Thesis. Una herramienta didáctica para el aprendizaje de semántica en lógica de predicados de primer orden.
C. L. Torres.
Director: M. V. Mauco. Co-director: E. Ferrante.
Universidad Nacional del Centro de la Provincia de Buenos Aires (UNICEN), Argentina (2016)
Engineering Degree Thesis. Aporte al desarrollo de aplicaciones interactivas en el Sistema Argentino de TV Digital Terrestre (SATVD-T).
M. F. Ochoa.
Director: C. García Bauza. Co-director: E. Ferrante.
Universidad Nacional del Centro de la Provincia de Buenos Aires (UNICEN), Argentina (2015)
Engineering Degree Thesis. Segmentación de imágenes médicas tridimensionales basada en indicadores de textura.
J. I. Orlando, H. L. Manterola.
Director: M. del Fresno. Co-director: E. Ferrante.
Universidad Nacional del Centro de la Provincia de Buenos Aires (UNICEN), Argentina (2013)