D
Derek L. G. Hill
Researcher at University College London
Publications - 286
Citations - 38648
Derek L. G. Hill is an academic researcher from University College London. The author has contributed to research in topics: Image registration & Imaging phantom. The author has an hindex of 77, co-authored 285 publications receiving 36657 citations. Previous affiliations of Derek L. G. Hill include Indiana University & Critical Path Institute.
Papers
More filters
Comparison of Threshold-Based Segmentation Methods on Pre- and Post-Therapy PET Scans.
TL;DR: Different segmentation methods were found to correlate well with each other for preand posttherapy tumour volume (TV) and total lesion glycolysis (TLG) but did not correlated as well for absolute change and % change of TV and TLG between preandPosttherapy images.
Use of Data Provenance and the Grid in Medical Image Analysis and Drug Discovery - An IXI Exemplar
Kelvin K. Leung,Mark Holden,RA Heckmann,N Saeed,Keith J. Brooks,J.B. Buckton,Kumar Changani,David G. Reid,Daniel Rueckert,Jo Hajnal,Derek L. G. Hill +10 more
TL;DR: This work applied image registration and visualisation techniques for quantitative and qualitative assessment of changes over time in an experimental model of rheumatoid arthritis, and used the Grid to enable remote invocation and parallel execution of the algorithms.
Proceedings ArticleDOI
Surface simplification for shape measurement: application to the human brain
TL;DR: A surface simplification method for discrete data representing surfaces derived from MR images is developed that facilitates the calculation of local measures of intrinsic curvature and folding while preserving the essential features of the surface in high curvature regions.
Posted ContentDOI
Plasma lipid and liporotein biomarkers in LBC1936: Do they predict general cognitive ability and brain structure?
Sarah E. Harris,Stuart J. Ritchie,Gonçalo D S Correia,Beatriz Jiménez,Chloe Fawns-Ritchie,Alison Pattie,Janie Corley,Maniega Sm,Maria del C. Valdés Hernández,John M. Starr,Derek L. G. Hill,Paul Bryan Wren,Mark E. Bastin,Matthew R. Lewis,Joanna M. Wardlaw,Ian J. Deary +15 more
TL;DR: Ultra-performance liquid chromatography mass spectrometry and nuclear magnetic resonance were used to measure targeted and untargeted metabolites, mainly lipids and lipoproteins in LBC1936 to identify sets of metabolites that predict variation in general cognitive ability and structural brain variables, but no metabolite set predicted cognitive ability, or white matter hyperintensities or connectivity.