608 citations · 637 across the 22 of their papers we have counts for
23 papers
Decoding Phenotypes: A Framework for Fusing Genomic Language Models and Neuroimaging
Tianli Tao, Ziyang Wang, Emma Robinson +2
Neuroimaging and genetic testing are two important clinical references for nervous system diseases, offering complementary diagnostic information. However, integrating genomic and…
Weakly Supervised Learning of Cortical Surface Reconstruction from Segmentations
Qiang Ma, Liu Li, Emma C. Robinson +2
Existing learning-based cortical surface reconstruction approaches heavily rely on the supervision of pseudo ground truth (pGT) cortical surfaces for training. Such pGT surfaces ar…
The Developing Human Connectome Project: A Fast Deep Learning-based Pipeline for Neonatal Cortical Surface Reconstruction
Qiang Ma, Kaili Liang, Liu Li +6
The Developing Human Connectome Project (dHCP) aims to explore developmental patterns of the human brain during the perinatal period. An automated processing pipeline has been deve…
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,…
Conditional Temporal Attention Networks for Neonatal Cortical Surface Reconstruction
Qiang Ma, Liu Li, Vanessa Kyriakopoulou +4
Cortical surface reconstruction plays a fundamental role in modeling the rapid brain development during the perinatal period. In this work, we propose Conditional Temporal Attentio…
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…