Search Results for author: Olivier Salvado

Found 6 papers, 1 papers with code

Learning Dense Correspondence from Synthetic Environments

no code implementations24 Mar 2022 Mithun Lal, Anthony Paproki, Nariman Habili, Lars Petersson, Olivier Salvado, Clinton Fookes

Results show that training 2D-3D mapping network models on synthetic data is a viable alternative to using real data.

CorticalFlow: A Diffeomorphic Mesh Transformer Network for Cortical Surface Reconstruction

no code implementations NeurIPS 2021 Leo Lebrat, Rodrigo Santa Cruz, Frederic de Gournay, Darren Fu, Pierrick Bourgeat, Jurgen Fripp, Clinton Fookes, Olivier Salvado

In this paper, we introduce CorticalFlow, a new geometric deep-learning model that, given a 3-dimensional image, learns to deform a reference template towards a targeted object.

Surface Reconstruction

MongeNet: Efficient Sampler for Geometric Deep Learning

1 code implementation CVPR 2021 Léo Lebrat, Rodrigo Santa Cruz, Clinton Fookes, Olivier Salvado

Recent advances in geometric deep-learning introduce complex computational challenges for evaluating the distance between meshes.

DeepCSR: A 3D Deep Learning Approach for Cortical Surface Reconstruction

no code implementations22 Oct 2020 Rodrigo Santa Cruz, Leo Lebrat, Pierrick Bourgeat, Clinton Fookes, Jurgen Fripp, Olivier Salvado

Having these limitations in mind, we propose DeepCSR, a 3D deep learning framework for cortical surface reconstruction from MRI.

Surface Reconstruction

Going deeper with brain morphometry using neural networks

no code implementations7 Sep 2020 Rodrigo Santa Cruz, Léo Lebrat, Pierrick Bourgeat, Vincent Doré, Jason Dowling, Jurgen Fripp, Clinton Fookes, Olivier Salvado

Brain morphometry from magnetic resonance imaging (MRI) is a consolidated biomarker for many neurodegenerative diseases.

A Multiple Decoder CNN for Inverse Consistent 3D Image Registration

no code implementations15 Feb 2020 Abdullah Nazib, Clinton Fookes, Olivier Salvado, Dimitri Perrin

The recent application of deep learning technologies in medical image registration has exponentially decreased the registration time and gradually increased registration accuracy when compared to their traditional counterparts.

Image Registration Medical Image Registration

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