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05/09/2023
Towards unraveling calibration biases in medical image analysis
In recent years the development of artificial intelligence (AI) systems ...
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05/02/2023
Are demographically invariant models and representations in medical imaging fair?
Medical imaging models have been shown to encode information about patie...
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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...
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02/07/2022
SUD: Supervision by Denoising for Medical Image Segmentation
Training a fully convolutional network for semantic segmentation typical...
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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...
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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...
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08/03/2021
Domain Generalization via Gradient Surgery
In real-life applications, machine learning models often face scenarios ...
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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...
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05/22/2021
Orthogonal Ensemble Networks for Biomedical Image Segmentation
Despite the astonishing performance of deep-learning based approaches fo...
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09/29/2020
Cranial Implant Design via Virtual Craniectomy with Shape Priors
Cranial implant design is a challenging task, whose accuracy is crucial ...
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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...
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07/07/2020
Self-supervised Skull Reconstruction in Brain CT Images with Decompressive Craniectomy
Decompressive craniectomy (DC) is a common surgical procedure consisting...
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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...
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01/20/2020
Learning Deformable Registration of Medical Images with Anatomical Constraints
Deformable image registration is a fundamental problem in the field of m...
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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...
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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...
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09/24/2018
Weakly-Supervised Learning of Metric Aggregations for Deformable Image Registration
Deformable registration has been one of the pillars of biomedical image ...
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08/23/2018
Left ventricle quantification through spatio-temporal CNNs
Cardiovascular diseases are among the leading causes of death globally. ...
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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...
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11/04/2017
Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation
Deep learning approaches such as convolutional neural nets have consiste...
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07/19/2017
Deformable Registration through Learning of Context-Specific Metric Aggregation
We propose a novel weakly supervised discriminative algorithm for learni...
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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...
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03/08/2017
Spectral Graph Convolutions for Population-based Disease Prediction
Exploiting the wealth of imaging and non-imaging information for disease...
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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...
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02/06/2017
Slice-to-volume medical image registration: a survey
During the last decades, the research community of medical imaging has w...
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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...
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02/05/2016