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Multimodal surface matching with higher-order smoothness constraints
2018
NeuroImage
Preserved Fulltext
The Multimodal Surface Matching (MSM) tool is a flexible, spherical registration approach that enables accurate registration of surfaces based on a variety of different features. ...
In brain imaging, accurate alignment of cortical surfaces is fundamental to the statistical sensitivity and spatial localisation of group studies, and cortical surface-based alignment has generally been ...
The Multimodal Surface Matching (MSM) tool is a flexible, spherical registration approach that enables accurate registration of surfaces based on a variety of different features. ...
doi:10.1016/j.neuroimage.2017.10.037
pmid:29100940
pmcid:PMC5991912
fatcat:dhrkgap4zbbe3cudmyy6ajvcme
MSM: A new flexible framework for Multimodal Surface Matching
2014
NeuroImage
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In this paper we demonstrate the utility of a new Multimodal Surface Matching (MSM) algorithm capable of driving alignment using a wide variety of descriptors of brain architecture, function and connectivity ...
We compare the results with two state of the art surface registration methods that use geometric features: FreeSurfer and Spherical Demons. ...
The framework is implemented using a fast, mul-tiresolution, discrete optimisation scheme, which offers significant speed-ups relative to the widely-used FreeSurfer surface registration method, while not ...
doi:10.1016/j.neuroimage.2014.05.069
pmid:24939340
pmcid:PMC4190319
fatcat:4zrkee5ttjb2jcndhq2rxts56i
Multimodal Surface Matching with Higher-Order Smoothness Constraints
[article]
2017
bioRxiv
pre-print
Preserved Fulltext
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The Multimodal Surface Matching (MSM) tool is a flexible, spherical registration approach that enables accurate registration of surfaces based on a variety of different features. ...
In brain imaging, accurate alignment of cortical surfaces is fundamental to the statistical sensitivity and spatial localisation of group studies; and cortical surface-based alignment has generally been ...
The Multimodal Surface Matching (MSM) tool is a flexible, spherical registration approach that enables accurate registration of surfaces based on a variety of different features. ...
doi:10.1101/178962
fatcat:h5lnr6h4wzbyxitdckyr74qlka
Benchmarking Geometric Deep Learning for Cortical Segmentation and Neurodevelopmental Phenotype Prediction
[article]
2021
bioRxiv
pre-print
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Several recent studies have explored the potential for using these techniques to analyse and segment the cortical surface. ...
This paper benchmarks a collection of geometric and traditional deep learning models on phenotype prediction and segmentation of sphericalised neonatal cortical surface data, from the publicly available ...
All registrations were performed using Multimodal Surface Matching (MSM) (Robinson et al., 2014 (Robinson et al., , 2018) ) driven by sulcal depth as the sole feature. ...
doi:10.1101/2021.12.01.470730
fatcat:szpev7wqenax7mds53ncg5stte
Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning
[article]
2021
arXiv
pre-print
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We used a complementary set of metrics, including robustness, accuracy, plausibility, and runtime, enabling unique insight into the current state-of-the-art of medical image registration. ...
Image registration is a fundamental medical image analysis task, and a wide variety of approaches have been proposed. ...
feature extraction, using an nnUNet, and a very fast and accurate conventional optimisation. ...
arXiv:2112.04489v2
fatcat:4hunhsm75bdkxipdwmngsdafjy
A Survey of Methods for 3D Histology Reconstruction
2018
Medical Image Analysis
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It is thereby possible to recover the original topology of histology and lost relationships, gain insight into what affects the signals used to construct medical images (and characterising them), or build ...
This paper reviews almost three decades of methods for 3D reconstruction from serial sections, used in the study of many different types of tissue. ...
Smriti Patodia, from UCL Institute of Neurology (Department of Neuropathology), for her comments on Section 2 and the images used in Figures ...
doi:10.1016/j.media.2018.02.004
pmid:29502034
fatcat:ta5hlvqjpzenxhltfwh6p4mhqq
Modelling the Neuroanatomical Progression of Alzheimer's Disease and Posterior Cortical Atrophy
[article]
2020
arXiv
pre-print
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My first contribution is a study on the progression of Posterior Cortical Atrophy, using models already developed: the Event-based Model (EBM) and the Differential Equation Model (DEM). ...
In this work I developed novel models of disease progression and applied them to estimate the progression of Alzheimer's disease and Posterior Cortical atrophy, a rare neurodegenerative syndrome causing ...
He has always encouraged me to pursue interesting ideas and supported me in developing them. ...
arXiv:2003.04805v1
fatcat:a5gmy75lvnfnhbtvztqoxikukm
The developing Human Connectome Project (dHCP) automated resting-state functional processing framework for newborn infants
2020
NeuroImage
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We provide a detailed description and evaluation of the pipeline which includes integrated slice-to-volume motion correction and dynamic susceptibility distortion correction, a robust multimodal registration ...
This is being achieved through the acquisition of multi-modal MRI data from over 1000 in- and ex-utero subjects combined with the development of optimised pre-processing pipelines. ...
Mark Chiew for advice on multi-band artefacts, and Assoc. Prof. Kenneth Pope for assistance with the neonatal HRF. ...
doi:10.1016/j.neuroimage.2020.117303
pmid:32866666
pmcid:PMC7762845
fatcat:f2xibrg5snfczhvwe2rruhd5cm
SynthSeg: Domain Randomisation for Segmentation of Brain Scans of any Contrast and Resolution
[article]
2021
arXiv
pre-print
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Finally, we demonstrate the generalisability of SynthSeg by applying it to cardiac MRI and CT segmentation. ...
Despite advances in data augmentation and transfer learning, convolutional neural networks (CNNs) difficultly generalise to unseen domains. ...
thus do not solve While these networks obtain fast and accurate segmen-
the general lack of generalisation of neural networks. ...
arXiv:2107.09559v2
fatcat:lxppdyslkffg7hxggk3ztcs73m
EEG and MEG Data Analysis in SPM8
2011
Computational Intelligence and Neuroscience
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based on the general linear model, with correction for multiple comparisons using random field theory; (ii) Bayesian M/EEG source reconstruction, including support for group studies, simultaneous EEG and ...
SPM8 is integrated with the FieldTrip toolbox , making it possible for users to combine a variety of standard analysis methods with new schemes implemented in SPM and build custom analysis tools using ...
The authors would like to thank all their colleagues and SPM coauthors who have contributed directly and indirectly to the software described in this paper. ...
doi:10.1155/2011/852961
pmid:21437221
pmcid:PMC3061292
fatcat:fpvvw7yr2vey5ic2kuqxi6axfe
3D shape matching and registration : a probabilistic perspective
[article]
2018
Preserved Fulltext
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Dense correspondence is a key area in computer vision and medical image analysis. It has applications in registration and shape analysis. ...
In this thesis, we use belief propagation to perform the probabilistic inference for 3D shape matching. ...
[83] present a rigid body registration approach based on an active surface model, which can be used for surface-to-3D images and surface-to-surface registration. ...
doi:10.25911/5d5155d7a4031
fatcat:3r7wqgpxhrhu5nmq3a5kqjiqba
Modeling & Analysis
2003
NeuroImage
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This anomaly has lead to the use of computer-based tools that create 2D cortical surfaces, which can be inflated, flattened, and overlaid with functional activation data. ...
This review provides a discussion of two freely available cortical surface modeling packages that have gained wide use in the field of neuroimaging: FreeSurfer [1, 2] and SureFit [3]. ...
We parameterize hippocampus surfaces using spherical harmonic (SPHARM) expansions [1]. Using more SPHARM coefficients leads to a more detailed surface reconstruction ( Figure 1 ). ...
doi:10.1016/s1053-8119(05)70006-9
fatcat:zff2suxcofbxvetfrwfwcxi3zm
The developing Human Connectome Project (dHCP) automated resting-state functional processing framework for newborn infants
[article]
2019
bioRxiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
We provide a detailed description and evaluation of the pipeline which includes integrated slice-to-volume motion correction and dynamic susceptibility distortion correction, a robust multimodal registration ...
This is being achieved through the acquisition of multi-modal MRI data from over 1000 in- and ex-utero subjects combined with the development of optimised pre-processing pipelines. ...
Acknowledgements We are grateful to Dr Mark Chiew for advice on multi-band artefacts, and Assoc. Prof. Kenneth Pope for assistance with the neonatal HRF. ...
doi:10.1101/766030
fatcat:j6xg3n7lfjhrrfujmpqf7juv54
Spatiotemporal organization of human sensorimotor beta burst activity
[article]
2022
bioRxiv
pre-print
Preserved Fulltext
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These burst events have been linked to a range of sensory and motor processes, but their precise spatial, spectral, and temporal structure remains unclear. ...
Finally, our results suggest that sensorimotor beta bursts occurring before and after a movement share the same generator but can be distinguished by their anatomical, spectral and spatiotemporal characteristics ...
Subject-specific head-casts optimise co-registration and reduce head movements, and thereby significantly improve the signal to noise ratio. ...
doi:10.1101/2022.05.19.492617
fatcat:3veme77rnzc5leffwjjw5drabm
Causal inference in the multisensory brain
[article]
2018
bioRxiv
pre-print
Preserved Fulltext
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association cortices, thereby framing multisensory integration in the generalised context of adaptive behaviour. ...
The brain could solve this challenge using a hierarchical principle, by deriving rapidly a fused sensory estimate for computational expediency and, later and if required, filtering out irrelevant signals ...
association cortices, thereby framing multisensory integration in the generalised context of adaptive behaviour. ...
doi:10.1101/500413
fatcat:qpsiyomeezfk5ft5ja3zhmsrp4
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