b'Enzo Ferrante'

DeepAI AI Chat

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research

∙ 05/09/2023

Towards unraveling calibration biases in medical image analysis

In recent years the development of artificial intelligence (AI) systems ...

7 María Agustina Ricci Lara, et al. ∙

research

∙ 05/02/2023

Are demographically invariant models and representations in medical imaging fair?

Medical imaging models have been shown to encode information about patie...

12 Eike Petersen, et al. ∙

research

∙ 01/07/2023

Unsupervised ensemble-based phenotyping helps enhance the discoverability of genes related to heart morphology

Recent genome-wide association studies (GWAS) have been successful in id...

10 Rodrigo Bonazzola, et al. ∙

research

∙ 02/07/2022

SUD: Supervision by Denoising for Medical Image Segmentation

Training a fully convolutional network for semantic segmentation typical...

5 Sean I. Young, et al. ∙

research

∙ 12/23/2021

Understanding the impact of class imbalance on the performance of chest x-ray image classifiers

This work aims to understand the impact of class imbalance on the perfor...

17 Candelaria Mosquera, et al. ∙

research

∙ 12/22/2021

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

Modern deep neural networks have achieved remarkable progress in medical...

8 Agostina Larrazabal, et al. ∙

research

∙ 08/03/2021

Domain Generalization via Gradient Surgery

In real-life applications, machine learning models often face scenarios ...

10 Lucas Mansilla, et al. ∙

research

∙ 06/17/2021

Hybrid graph convolutional neural networks for landmark-based anatomical segmentation

In this work we address the problem of landmark-based segmentation for a...

9 Nicolás Gaggion, et al. ∙

research

∙ 05/22/2021

Orthogonal Ensemble Networks for Biomedical Image Segmentation

Despite the astonishing performance of deep-learning based approaches fo...

37 Agostina J. Larrazabal, et al. ∙

research

∙ 09/29/2020

Cranial Implant Design via Virtual Craniectomy with Shape Priors

Cranial implant design is a challenging task, whose accuracy is crucial ...

8 Franco Matzkin, et al. ∙

research

∙ 09/10/2020

Unsupervised Domain Adaptation via CycleGAN for White Matter Hyperintensity Segmentation in Multicenter MR Images

Automatic segmentation of white matter hyperintensities in magnetic reso...

19 Julian Alberto Palladino, et al. ∙

research

∙ 07/07/2020

Self-supervised Skull Reconstruction in Brain CT Images with Decompressive Craniectomy

Decompressive craniectomy (DC) is a common surgical procedure consisting...

13 Franco Matzkin, et al. ∙

research

∙ 06/24/2020

Post-DAE: Anatomically Plausible Segmentation via Post-Processing with Denoising Autoencoders

We introduce Post-DAE, a post-processing method based on denoising autoe...

1 Agostina J. Larrazabal, et al. ∙

research

∙ 01/20/2020

Learning Deformable Registration of Medical Images with Anatomical Constraints

Deformable image registration is a fundamental problem in the field of m...

13 Lucas Mansilla, et al. ∙

research

∙ 06/05/2019

Anatomical Priors for Image Segmentation via Post-Processing with Denoising Autoencoders

Deep convolutional neural networks (CNN) proved to be highly accurate to...

0 Agostina J. Larrazabal, et al. ∙

research

∙ 03/08/2019

Joint Learning of Brain Lesion and Anatomy Segmentation from Heterogeneous Datasets

Brain lesion and anatomy segmentation in magnetic resonance images are f...

0 Nicolas Roulet, et al. ∙

research

∙ 09/24/2018

Weakly-Supervised Learning of Metric Aggregations for Deformable Image Registration

Deformable registration has been one of the pillars of biomedical image ...

2 Enzo Ferrante, et al. ∙

research

∙ 08/23/2018

Left ventricle quantification through spatio-temporal CNNs

Cardiovascular diseases are among the leading causes of death globally. ...

0 Alejandro Debus, et al. ∙

research

∙ 06/05/2018

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

Graphs are widely used as a natural framework that captures interactions...

0 Sarah Parisot, et al. ∙

research

∙ 11/04/2017

Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation

Deep learning approaches such as convolutional neural nets have consiste...

0 Konstantinos Kamnitsas, et al. ∙

research

∙ 07/19/2017

Deformable Registration through Learning of Context-Specific Metric Aggregation

We propose a novel weakly supervised discriminative algorithm for learni...

0 Enzo Ferrante, et al. ∙

research

∙ 05/22/2017

Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation

Incorporation of prior knowledge about organ shape and location is key t...

0 Ozan Oktay, et al. ∙

research

∙ 03/08/2017

Spectral Graph Convolutions for Population-based Disease Prediction

Exploiting the wealth of imaging and non-imaging information for disease...

0 Sarah Parisot, et al. ∙

research

∙ 03/07/2017

Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks

Evaluating similarity between graphs is of major importance in several c...

0 Ira Ktena, et al. ∙

research

∙ 02/06/2017

Slice-to-volume medical image registration: a survey

During the last decades, the research community of medical imaging has w...

0 Enzo Ferrante, et al. ∙

research

∙ 08/19/2016

Rigid Slice-To-Volume Medical Image Registration through Markov Random Fields

Rigid slice-to-volume registration is a challenging task, which finds ap...

0 Roque Porchetto, et al. ∙

research

∙ 02/05/2016

Sub-cortical brain structure segmentation using F-CNN's

In this paper we propose a deep learning approach for segmenting sub-cor...

0 Mahsa Shakeri, et al. ∙