Enzo Ferrante

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Universidad Nacional del Litoral ∙ Imperial College London

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Cranial Implant Design via Virtual Craniectomy with Shape Priors

Cranial implant design is a challenging task, whose accuracy is crucial ...
09/29/2020 ∙ by Franco Matzkin, et al. ∙ 8 ∙ share

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

Automatic segmentation of white matter hyperintensities in magnetic reso...
09/10/2020 ∙ by Julian Alberto Palladino, et al. ∙ 19 ∙ share

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

Decompressive craniectomy (DC) is a common surgical procedure consisting...
07/07/2020 ∙ by Franco Matzkin, et al. ∙ 13 ∙ share

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

We introduce Post-DAE, a post-processing method based on denoising autoe...
06/24/2020 ∙ by Agostina J. Larrazabal, et al. ∙ 1 ∙ share

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Learning Deformable Registration of Medical Images with Anatomical Constraints

Deformable image registration is a fundamental problem in the field of m...
01/20/2020 ∙ by Lucas Mansilla, et al. ∙ 13 ∙ share

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

Deep convolutional neural networks (CNN) proved to be highly accurate to...
06/05/2019 ∙ by Agostina J. Larrazabal, et al. ∙ 0 ∙ share

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Joint Learning of Brain Lesion and Anatomy Segmentation from Heterogeneous Datasets

Brain lesion and anatomy segmentation in magnetic resonance images are f...
03/08/2019 ∙ by Nicolas Roulet, et al. ∙ 0 ∙ share

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Weakly-Supervised Learning of Metric Aggregations for Deformable Image Registration

Deformable registration has been one of the pillars of biomedical image ...
09/24/2018 ∙ by Enzo Ferrante, et al. ∙ 2 ∙ share

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Left ventricle quantification through spatio-temporal CNNs

Cardiovascular diseases are among the leading causes of death globally. ...
08/23/2018 ∙ by Alejandro Debus, et al. ∙ 0 ∙ share

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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...
06/05/2018 ∙ by Sarah Parisot, et al. ∙ 0 ∙ share

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Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation

Deep learning approaches such as convolutional neural nets have consiste...
11/04/2017 ∙ by Konstantinos Kamnitsas, et al. ∙ 0 ∙ share

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Deformable Registration through Learning of Context-Specific Metric Aggregation

We propose a novel weakly supervised discriminative algorithm for learni...
07/19/2017 ∙ by Enzo Ferrante, et al. ∙ 0 ∙ share

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

Incorporation of prior knowledge about organ shape and location is key t...
05/22/2017 ∙ by Ozan Oktay, et al. ∙ 0 ∙ share

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Spectral Graph Convolutions for Population-based Disease Prediction

Exploiting the wealth of imaging and non-imaging information for disease...
03/08/2017 ∙ by Sarah Parisot, et al. ∙ 0 ∙ share

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

Evaluating similarity between graphs is of major importance in several c...
03/07/2017 ∙ by Ira Ktena, et al. ∙ 0 ∙ share

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Slice-to-volume medical image registration: a survey

During the last decades, the research community of medical imaging has w...
02/06/2017 ∙ by Enzo Ferrante, et al. ∙ 0 ∙ share

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

Rigid slice-to-volume registration is a challenging task, which finds ap...
08/19/2016 ∙ by Roque Porchetto, et al. ∙ 0 ∙ share

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

In this paper we propose a deep learning approach for segmenting sub-cor...
02/05/2016 ∙ by Mahsa Shakeri, et al. ∙ 0 ∙ share

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