2 citations · 4 across the 6 of their papers we have counts for
6 papers
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.…
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…
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…