563 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University College LondonGB37 papers
- National Hospital for Neurology and NeurosurgeryGB15 papers
- Newcastle UniversityGB10 papers
- Wellcome Centre for Human NeuroimagingGB8 papers
- King's College LondonGB4 papers
- Queen Mary University of LondonGB4 papers
- Harvard UniversityUS3 papers
- Imperial College LondonGB3 papers
- Centre National de la Recherche ScientifiqueFR2 papers
- Humboldt-Universität zu BerlinDE2 papers
- Max Planck Institute for Human Cognitive and Brain SciencesDE2 papers
- National Institute for Health and Care ResearchGB2 papers
9 papers · 1 filter
Evaluation of Uncertainty-Aware Multi-Software Ensembles for Hippocampal Segmentation
Gabriel Oliveira-Stahl, Anna Schroder, James Moggridge +6
Accurate hippocampal segmentation can be a useful tool for diagnosing and monitoring neurological conditions such as Alzheimer's disease and epilepsy. While numerous automated segm…
Brain tumour segmentation with incomplete imaging data
James K Ruffle, Samia Mohinta, Robert J Gray +2
The complex heterogeneity of brain tumours is increasingly recognized to demand data of magnitudes and richness only fully-inclusive, large-scale collections drawn from routine cli…
Vessel-CAPTCHA: an efficient learning framework for vessel annotation and segmentation
Vien Ngoc Dang, Francesco Galati, Rosa Cortese +7
Deep learning techniques for 3D brain vessel image segmentation have not been as successful as in the segmentation of other organs and tissues. This can be explained by two factors…
Flexible Bayesian Modelling for Nonlinear Image Registration
Mikael Brudfors, Yaël Balbastre, Guillaume Flandin +2
We describe a diffeomorphic registration algorithm that allows groups of images to be accurately aligned to a common space, which we intend to incorporate into the SPM software. Th…
Grey matter sublayer thickness estimation in themouse cerebellum
Da Ma, Manuel J. Cardoso, Maria A. Zuluaga +7
The cerebellar grey matter morphology is an important feature to study neurodegenerative diseases such as Alzheimer's disease or Down's syndrome. Its volume or thickness is commonl…
Elastic Registration of Geodesic Vascular Graphs
Stefano Moriconi, Maria A. Zuluaga, H. Rolf Jager +3
Vascular graphs can embed a number of high-level features, from morphological parameters, to functional biomarkers, and represent an invaluable tool for longitudinal and cross-sect…
An Algorithm for Learning Shape and Appearance Models without Annotations
John Ashburner, Mikael Brudfors, Kevin Bronik +1
This paper presents a framework for automatically learning shape and appearance models for medical (and certain other) images. It is based on the idea that having a more accurate s…
VTrails: Inferring Vessels with Geodesic Connectivity Trees
Stefano Moriconi, Maria A. Zuluaga, H. Rolf Jäger +3
The analysis of vessel morphology and connectivity has an impact on a number of cardiovascular and neurovascular applications by providing patient-specific high-level quantitative…
NiftyNet: a deep-learning platform for medical imaging
Eli Gibson, Wenqi Li, Carole Sudre +14
Medical image analysis and computer-assisted intervention problems are increasingly being addressed with deep-learning-based solutions. Established deep-learning platforms are flex…