Search Results for author: Pierrick Bourgeat

Found 6 papers, 2 papers with code

CorticalFlow$^{++}$: Boosting Cortical Surface Reconstruction Accuracy, Regularity, and Interoperability

no code implementations14 Jun 2022 Rodrigo Santa Cruz, Léo Lebrat, Darren Fu, Pierrick Bourgeat, Jurgen Fripp, Clinton Fookes, Olivier Salvado

Using the state-of-the-art CorticalFlow model as a blueprint, this paper proposes three modifications to improve its accuracy and interoperability with existing surface analysis tools, while not sacrificing its fast inference time and low GPU memory consumption.

Surface Reconstruction

CorticalFlow: A Diffeomorphic Mesh Deformation Module for Cortical Surface Reconstruction

no code implementations6 Jun 2022 Léo Lebrat, Rodrigo Santa Cruz, Frédéric 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

CorticalFlow: A Diffeomorphic Mesh Transformer Network for Cortical Surface Reconstruction

1 code implementation 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

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.

Enforcing temporal consistency in Deep Learning segmentation of brain MR images

3 code implementations13 Jun 2019 Malav Bateriwala, Pierrick Bourgeat

Proposed CNN based segmentation approaches demonstrate how 2D segmentation using prior slices can provide similar results to 3D segmentation while maintaining good continuity in the 3D dimension and improved speed.

3D Medical Imaging Segmentation 4D Spatio Temporal Semantic Segmentation +2

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