output
20082026
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 q-bio.QMShow all

7 papers · 1 filter

q-bio.QM2025★ 1 cited

Parallelism in Neurodegenerative Biomarker Tests: Hidden Errors and the Risk of Misconduct

Axel Petzold, Joachim Pum, David P Crabb

Biomarkers are critical tools in the diagnosis and monitoring of neurodegenerative diseases. Reliable quantification depends on assay validity, especially the demonstration of para…

q-bio.QM2024★ 5 cited

VASARI-auto: equitable, efficient, and economical featurisation of glioma MRI

James K Ruffle, Samia Mohinta, Kelly Pegoretti Baruteau +5

The VASARI MRI feature set is a quantitative system designed to standardise glioma imaging descriptions. Though effective, deriving VASARI is time-consuming and seldom used in clin…

q-bio.QM2023★ 1 cited

Individualized prescriptive inference in ischaemic stroke

Dominic Giles, Chris Foulon, Guilherme Pombo +8

The gold standard in the treatment of ischaemic stroke is set by evidence from randomized controlled trials, based on simple descriptions of presumptively homogeneous populations.…

q-bio.QM2021★ 2 cited

Machine Learning and Glioblastoma: Treatment Response Monitoring Biomarkers in 2021

Thomas Booth, Bernice Akpinar, Andrei Roman +10

The aim of the systematic review was to assess recently published studies on diagnostic test accuracy of glioblastoma treatment response monitoring biomarkers in adults, developed…

q-bio.QM2019★ 467 cited

A tutorial on group effective connectivity analysis, part 2: second level analysis with PEB

Peter Zeidman, Amirhossein Jafarian, Mohamed L. Seghier +4

This tutorial provides a worked example of using Dynamic Causal Modelling (DCM) and Parametric Empirical Bayes (PEB) to characterise inter-subject variability in neural circuitry (…

q-bio.QM2019★ 419 cited

A tutorial on group effective connectivity analysis, part 1: first level analysis with DCM for fMRI

Peter Zeidman, Amirhossein Jafarian, Nadège Corbin +4

Dynamic Causal Modelling (DCM) is the predominant method for inferring effective connectivity from neuroimaging data. In the 15 years since its introduction, the neural models and…

q-bio.QM2008★ 2 cited

MIC: Mutual Information based hierarchical Clustering

Alexander Kraskov, Peter Grassberger

Clustering is a concept used in a huge variety of applications. We review a conceptually very simple algorithm for hierarchical clustering called in the following the {\it mutual i…