Enzo Ferrante
Orcid: 0000-0002-8500-788XAffiliations:
- CONICET-UNL, Santa Fe, Argentina
According to our database1,
Enzo Ferrante
authored at least 62 papers
between 2013 and 2024.
Collaborative distances:
Collaborative distances:
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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
CoRR, 2024
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024
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
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
Proceedings of the Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging, 2023
Proceedings of the Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging, 2023
2022
2021
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
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
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
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
Proceedings of the Towards the Automatization of Cranial Implant Design in Cranioplasty, 2020
2019
IEEE J. Biomed. Health Informatics, 2019
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
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
NeuroImage, 2018
Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer's disease.
Medical Image Anal., 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
Proceedings of the Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges, 2018
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018
2017
CoRR, 2017
Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation.
CoRR, 2017
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
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2017
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
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016
Proceedings of the Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging, 2016
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2016
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
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, 2013