Search Results for author: Jurgen Fripp

Found 7 papers, 1 papers with code

Automated volumetric and statistical shape assessment of cam-type morphology of the femoral head-neck region from 3D magnetic resonance images

no code implementations6 Dec 2021 Jessica M. Bugeja, Ying Xia, Shekhar S. Chandra, Nicholas J. Murphy, Jillian Eyles, Libby Spiers, Stuart Crozier, David J. Hunter, Jurgen Fripp, Craig Engstrom

Automated analyses of 3D MR images from patients with FAI using the CamMorph pipeline showed that, in comparison with female patients, male patients had significantly greater cam volume, surface area and height.

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

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.

Fabric Image Representation Encoding Networks for Large-scale 3D Medical Image Analysis

1 code implementation28 Jun 2020 Siyu Liu, Wei Dai, Craig Engstrom, Jurgen Fripp, Peter B. Greer, Stuart Crozier, Jason A. Dowling, Shekhar S. Chandra

In this work, a novel 3D segmentation network, Fabric Image Representation Networks (FIRENet), is proposed to extract and encode generalisable feature representations from multiple medical image datasets in a large-scale manner.

Semantic Segmentation Transfer Learning

3D Scanning System for Automatic High-Resolution Plant Phenotyping

no code implementations26 Feb 2017 Chuong V. Nguyen, Jurgen Fripp, David R. Lovell, Robert Furbank, Peter Kuffner, Helen Daily, Xavier Sirault

We assessed the system's accuracy using a 3D visual hull reconstruction algorithm applied on 2 plastic models of dicotyledonous plants, 2 sorghum plants and 2 wheat plants across different sets of tilt angles.

3D Reconstruction Camera Calibration

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