Search Results for author:
Found 6 papers, 2 papers with code
Enforcing temporal consistency in Deep Learning segmentation of brain MR images
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
+3
Going deeper with brain morphometry using neural networks
Brain morphometry from magnetic resonance imaging (MRI) is a consolidated biomarker for many neurodegenerative diseases.
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.
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.
CorticalFlow: A Diffeomorphic Mesh Deformation Module 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.
CorticalFlow$^{++}$: Boosting Cortical Surface Reconstruction Accuracy, Regularity, and Interoperability
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.
