research
∙
07/03/2023
Patch-CNN: Training data-efficient deep learning for high-fidelity diffusion tensor estimation from minimal diffusion protocols
We propose a new method, Patch-CNN, for diffusion tensor (DT) estimation...
share
research
∙
05/27/2023
Deep Variational Lesion-Deficit Mapping
Causal mapping of the functional organisation of the human brain require...
research
∙
07/01/2022
How can spherical CNNs benefit ML-based diffusion MRI parameter estimation?
This paper demonstrates spherical convolutional neural networks (S-CNN) ...
research
∙
06/07/2022
Fast Unsupervised Brain Anomaly Detection and Segmentation with Diffusion Models
Deep generative models have emerged as promising tools for detecting arb...
research
∙
11/29/2021
Equitable modelling of brain imaging by counterfactual augmentation with morphologically constrained 3D deep generative models
We describe Countersynth, a conditional generative model of diffeomorphi...
research
∙
11/24/2021
Hierarchical Graph-Convolutional Variational AutoEncoding for Generative Modelling of Human Motion
Models of human motion commonly focus either on trajectory prediction or...
research
∙
07/21/2021
An artificial intelligence natural language processing pipeline for information extraction in neuroradiology
The use of electronic health records in medical research is difficult be...
research
∙
07/17/2020
iNNk: A Multi-Player Game to Deceive a Neural Network
This paper presents iNNK, a multiplayer drawing game where human players...
research
∙
07/26/2019
Bayesian Volumetric Autoregressive generative models for better semisupervised learning
Deep generative models are rapidly gaining traction in medical imaging. ...
research
∙
09/11/2017