Enzo Ferrante

Orcid: 0000-0002-8500-788X

Affiliations:
  • CONICET-UNL, Santa Fe, Argentina


According to our database1, Enzo Ferrante authored at least 62 papers between 2013 and 2024.

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Bibliography

2024
Demographically-Informed Prediction Discrepancy Index: Early Warnings of Demographic Biases for Unlabeled Populations.
Trans. Mach. Learn. Res., 2024

Unsupervised ensemble-based phenotyping enhances discoverability of genes related to left-ventricular morphology.
Nat. Mac. Intell., 2024

SignAttention: On the Interpretability of Transformer Models for Sign Language Translation.
CoRR, 2024

Open Challenges on Fairness of Artificial Intelligence in Medical Imaging Applications.
CoRR, 2024

Uncertainty in latent representations of variational autoencoders optimized for visual tasks.
CoRR, 2024

Predicting risk of cardiovascular disease using retinal OCT imaging.
CoRR, 2024

Source Matters: Source Dataset Impact on Model Robustness in Medical Imaging.
CoRR, 2024

Deep Vessel Segmentation with Joint Multi-Prior Encoding.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Fitting Skeletal Models via Graph-Based Learning.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

ViG-Bias: Visually Grounded Bias Discovery and Mitigation.
Proceedings of the Computer Vision - ECCV 2024, 2024

2023
Improving Anatomical Plausibility in Medical Image Segmentation via Hybrid Graph Neural Networks: Applications to Chest X-Ray Analysis.
IEEE Trans. Medical Imaging, February, 2023

Multi-view Hybrid Graph Convolutional Network for Volume-to-mesh Reconstruction in Cardiovascular MRI.
CoRR, 2023

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare.
CoRR, 2023

CheXmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray images.
CoRR, 2023

Are demographically invariant models and representations in medical imaging fair?
CoRR, 2023

Unsupervised ensemble-based phenotyping helps enhance the discoverability of genes related to heart morphology.
CoRR, 2023

Maximum Entropy on Erroneous Predictions: Improving Model Calibration for Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Multi-Center Anatomical Segmentation with Heterogeneous Labels Via Landmark-Based Models.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Towards Unraveling Calibration Biases in Medical Image Analysis.
Proceedings of the Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging, 2023

Unsupervised Bias Discovery in Medical Image Segmentation.
Proceedings of the Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging, 2023

2022
SUD: Supervision by Denoising for Medical Image Segmentation.
CoRR, 2022

2021
AutoImplant 2020-First MICCAI Challenge on Automatic Cranial Implant Design.
IEEE Trans. Medical Imaging, 2021

Left Ventricle Quantification Challenge: A Comprehensive Comparison and Evaluation of Segmentation and Regression for Mid-Ventricular Short-Axis Cardiac MR Data.
IEEE J. Biomed. Health Informatics, 2021

Understanding the impact of class imbalance on the performance of chest x-ray image classifiers.
CoRR, 2021

Maximum Entropy on Erroneous Predictions (MEEP): Improving model calibration for medical image segmentation.
CoRR, 2021

Orthogonal Ensemble Networks for Biomedical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Hybrid Graph Convolutional Neural Networks for Landmark-Based Anatomical Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Image-Derived Phenotype Extraction for Genetic Discovery via Unsupervised Deep Learning in CMR Images.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Domain Generalization via Gradient Surgery.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Post-DAE: Anatomically Plausible Segmentation via Post-Processing With Denoising Autoencoders.
IEEE Trans. Medical Imaging, 2020

Learning deformable registration of medical images with anatomical constraints.
Neural Networks, 2020

Unsupervised Domain Adaptation via CycleGAN for White Matter Hyperintensity Segmentation in Multicenter MR Images.
CoRR, 2020

Self-supervised Skull Reconstruction in Brain CT Images with Decompressive Craniectomy.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Cranial Implant Design via Virtual Craniectomy with Shape Priors.
Proceedings of the Towards the Automatization of Cranial Implant Design in Cranioplasty, 2020

2019
Weakly Supervised Learning of Metric Aggregations for Deformable Image Registration.
IEEE J. Biomed. Health Informatics, 2019

Joint Learning of Brain Lesion and Anatomy Segmentation from Heterogeneous Datasets.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2019

Anatomical Priors for Image Segmentation via Post-processing with Denoising Autoencoders.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

TBI Lesion Segmentation in Head CT: Impact of Preprocessing and Data Augmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019

2018
Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and Segmentation.
IEEE Trans. Medical Imaging, 2018

Metric learning with spectral graph convolutions on brain connectivity networks.
NeuroImage, 2018

Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer's disease.
Medical Image Anal., 2018

Graph-Based Slice-to-Volume Deformable Registration.
Int. J. Comput. Vis., 2018

Disease Prediction using Graph Convolutional Networks: Application to Autism Spectrum Disorder and Alzheimer's Disease.
CoRR, 2018

On the Adaptability of Unsupervised CNN-Based Deformable Image Registration to Unseen Image Domains.
Proceedings of the Machine Learning in Medical Imaging - 9th International Workshop, 2018

Left Ventricle Quantification Through Spatio-Temporal CNNs.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges, 2018

Deep learning with ultrasound physics for fetal skull segmentation.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

2017
Slice-to-volume medical image registration: A survey.
Medical Image Anal., 2017

Arabidopsis roots segmentation based on morphological operations and CRFs.
CoRR, 2017

Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation.
CoRR, 2017

Spectral Graph Convolutions for Population-Based Disease Prediction.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

Distance Metric Learning Using Graph Convolutional Networks: Application to Functional Brain Networks.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2017

Deformable Registration Through Learning of Context-Specific Metric Aggregation.
Proceedings of the Machine Learning in Medical Imaging - 8th International Workshop, 2017

2016
Graph-based deformable registration : slice-to-volume mapping and context specific methods. (Recalage déformable à base de graphes : mise en correspondance coupe-vers-volume et méthodes contextuelles).
PhD thesis, 2016

(Hyper)-graphical models in biomedical image analysis.
Medical Image Anal., 2016

Prior-Based Coregistration and Cosegmentation.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

Rigid Slice-To-Volume Medical Image Registration Through Markov Random Fields.
Proceedings of the Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging, 2016

DeepMedic for Brain Tumor Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2016

Sub-cortical brain structure segmentation using F-CNN'S.
Proceedings of the 13th IEEE International Symposium on Biomedical Imaging, 2016

2015
Slice-to-volume deformable registration: efficient one-shot consensus between plane selection and in-plane deformation.
Int. J. Comput. Assist. Radiol. Surg., 2015

Implicit planar and in-plane deformable mapping in medical images through high order graphs.
Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015

2013
Non-rigid 2D-3D Medical Image Registration Using Markov Random Fields.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, 2013


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