Imperial College London
Alternate

ProfessorDanielRueckert

Faculty of Engineering, Department of Computing

Professor of Visual Information Processing
 
 
 
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Contact

 

+44 (0)20 7594 8333d.rueckert Website

 
 
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Location

 

568Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Dahan:2022,
author = {Dahan, S and Fawaz, A and Williams, LZJ and Yang, C and Coalson, TS and Glasser, MF and Edwards, AD and Rueckert, D and Robinson, EC},
pages = {282--303},
title = {Surface Vision Transformers: Attention-Based Modelling applied to Cortical Analysis},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - 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 limitations resulting in poor modelling of long-range associations, as the generalisation of convolutions to irregular surfaces is non-trivial. Motivated by the success of attention-modelling in computer vision, we translate convolution-free vision transformer approaches to surface data, to introduce a domain-agnostic architecture to study any surface data projected onto a spherical manifold. Here, surface patching is achieved by representing spherical data as a sequence of triangular patches, extracted from a subdivided icosphere. A transformer model encodes the sequence of patches via successive multi-head self-attention layers while preserving the sequence resolution. We validate the performance of the proposed Surface Vision Transformer (SiT) on the task of phenotype regression from cortical surface metrics derived from the Developing Human Connectome Project (dHCP). Experiments show that the SiT generally outperforms surface CNNs, while performing comparably on registered and unregistered data. Analysis of transformer attention maps offers strong potential to characterise subtle cognitive developmental patterns.
AU  - Dahan,S
AU  - Fawaz,A
AU  - Williams,LZJ
AU  - Yang,C
AU  - Coalson,TS
AU  - Glasser,MF
AU  - Edwards,AD
AU  - Rueckert,D
AU  - Robinson,EC
EP  - 303
PY  - 2022///
SP  - 282
TI  - Surface Vision Transformers: Attention-Based Modelling applied to Cortical Analysis
ER  -
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