output
20102026
most citedNiftyNet: a deep-learning platform for medical imaging

563 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing 2018Show all

7 papers · 1 filter

cs.CV2018★ 5 cited

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…

cs.CV2018★ 12 cited

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…

q-bio.NC2018★ 28 cited

Computer modelling of connectivity change suggests epileptogenesis mechanisms in idiopathic generalised epilepsy

Nishant Sinha, Yujiang Wang, Justin Dauwels +4

Patients with idiopathic generalised epilepsy (IGE) typically have normal conventional magnetic resonance imaging (MRI), hence MRI based diagnosis is challenging. Anatomical abnorm…

q-bio.NC2018★ 38 cited

Universality in human cortical folding across lobes of individual brains

Yujiang Wang, Joe Necus, Luis Peraza Rodriguez +2

Background: We have previously demonstrated that cortical folding across mammalian species follows a universal scaling law that can be derived from a simple theoretical model. The…

cs.CV2018★ 12 cited

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…

q-bio.NC2018★ 59 cited

Fractal and Multifractal Properties of Electrographic Recordings of Human Brain Activity: Toward Its Use as a Signal Feature for Machine Learning in Clinical Applications

Lucas G. S. França, José G. V. Miranda, Marco Leite +4

The brain is a system operating on multiple time scales, and characterisation of dynamics across time scales remains a challenge. One framework to study such dynamics is that of fr…

stat.AP2018★ 20 cited

Optimising data for modelling neuronal responses

Peter Zeidman, Samira M Kazan, Nick Todd +3

In this technical note, we address an unresolved challenge in neuroimaging statistics: how to determine which of several datasets is the best for inferring neuronal responses. Comp…