6 citations · 12 across the 13 of their papers we have counts for
13 papers
SIM: Surface-based fMRI Analysis for Inter-Subject Multimodal Decoding from Movie-Watching Experiments
Simon Dahan, Gabriel Bénédict, Logan Z. J. Williams +4
Current AI frameworks for brain decoding and encoding, typically train and test models within the same datasets. This limits their utility for brain computer interfaces (BCI) or ne…
Cortical Surface Diffusion Generative Models
Zhenshan Xie, Simon Dahan, Logan Z. J. Williams +2
Cortical surface analysis has gained increased prominence, given its potential implications for neurological and developmental disorders. Traditional vision diffusion models, while…
Unsupervised Multimodal Surface Registration with Geometric Deep Learning
Mohamed A. Suliman, Logan Z. J. Williams, Abdulah Fawaz +1
This paper introduces GeoMorph, a novel geometric deep-learning framework designed for image registration of cortical surfaces. The registration process consists of two main steps.…
Spatio-Temporal Encoding of Brain Dynamics with Surface Masked Autoencoders
Simon Dahan, Logan Z. J. Williams, Yourong Guo +2
The development of robust and generalisable models for encoding the spatio-temporal dynamics of human brain activity is crucial for advancing neuroscientific discoveries. However,…
Robust and Generalisable Segmentation of Subtle Epilepsy-causing Lesions: a Graph Convolutional Approach
Hannah Spitzer, Mathilde Ripart, Abdulah Fawaz +6
Focal cortical dysplasia (FCD) is a leading cause of drug-resistant focal epilepsy, which can be cured by surgery. These lesions are extremely subtle and often missed even by exper…
The Multiscale Surface Vision Transformer
Simon Dahan, Logan Z. J. Williams, Daniel Rueckert +1
Surface meshes are a favoured domain for representing structural and functional information on the human cortex, but their complex topology and geometry pose significant challenges…
A Deep Generative Model of Neonatal Cortical Surface Development
Abdulah Fawaz, Logan Z. Williams, A. David Edwards +1
The neonatal cortical surface is known to be affected by preterm birth, and the subsequent changes to cortical organisation have been associated with poorer neurodevelopmental outc…
Surface Analysis with Vision Transformers
Simon Dahan, Logan Z. J. Williams, Abdulah Fawaz +2
The extension of convolutional neural networks (CNNs) to non-Euclidean geometries has led to multiple frameworks for studying manifolds. Many of those methods have shown design lim…
Surface Vision Transformers: Flexible Attention-Based Modelling of Biomedical Surfaces
Simon Dahan, Hao Xu, Logan Z. J. Williams +10
Recent state-of-the-art performances of Vision Transformers (ViT) in computer vision tasks demonstrate that a general-purpose architecture, which implements long-range self-attenti…
Surface Vision Transformers: Attention-Based Modelling applied to Cortical Analysis
Simon Dahan, Abdulah Fawaz, Logan Z. J. Williams +6
The extension of convolutional neural networks (CNNs) to non-Euclidean geometries has led to multiple frameworks for studying manifolds. Many of those methods have shown design lim…
A Deep-Discrete Learning Framework for Spherical Surface Registration
Mohamed A. Suliman, Logan Z. J. Williams, Abdulah Fawaz +1
Cortical surface registration is a fundamental tool for neuroimaging analysis that has been shown to improve the alignment of functional regions relative to volumetric approaches.…
Improving Phenotype Prediction using Long-Range Spatio-Temporal Dynamics of Functional Connectivity
Simon Dahan, Logan Z. J. Williams, Daniel Rueckert +1
The study of functional brain connectivity (FC) is important for understanding the underlying mechanisms of many psychiatric disorders. Many recent analyses adopt graph convolution…
ICAM-reg: Interpretable Classification and Regression with Feature Attribution for Mapping Neurological Phenotypes in Individual Scans
Cher Bass, Mariana da Silva, Carole Sudre +7
An important goal of medical imaging is to be able to precisely detect patterns of disease specific to individual scans; however, this is challenged in brain imaging by the degree…