Search Results for author:
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
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
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.
DeepCSR: A 3D Deep Learning Approach for Cortical Surface Reconstruction
Having these limitations in mind, we propose DeepCSR, a 3D deep learning framework for cortical surface reconstruction from MRI.
Medical Image Harmonization Using Deep Learning Based Canonical Mapping: Toward Robust and Generalizable Learning in Imaging
Conventional and deep learning-based methods have shown great potential in the medical imaging domain, as means for deriving diagnostic, prognostic, and predictive biomarkers, and by contributing to precision medicine.
Going deeper with brain morphometry using neural networks
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
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.
3D Scanning System for Automatic High-Resolution Plant Phenotyping
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.
