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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
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Journal ArticleDOI

Visualization and tracking of an inflatable balloon catheter using SSFP in a flow phantom and in the heart and great vessels of patients.

TL;DR: Although only the tip of the catheter was visualized, this technique proved to be effective in patients undergoing cardiac catheterization and demonstrated that it was advantageous to sacrifice spatial resolution in order to increase temporal resolution.
Proceedings ArticleDOI

Automated 3D registration of truncated MR and CT images of the head

TL;DR: It is shown that by limiting the measures to intra-cranial regions of the images, not containing deformable skin surface features, a greater accuracy may be provided for certain types of truncated image.
Journal ArticleDOI

Search for supersymmetric particles using acoplanar charged-particle pairs from Z0 decays

D. Decamp, +367 more
- 08 Feb 1990 - 
TL;DR: In this paper, a search for supersymmetric particles using acoplanar pairs of oppositely-charged particles in decays of the Z0 peak was performed, where approximately four are expected from background, allowing limits to be extended on combined photino and slepton masses.
Journal ArticleDOI

Quantification of small cerebral ventricular volume changes in treated growth hormone patients using nonrigid registration

TL;DR: A nonrigid registration algorithm based on optimising normalized mutual information to quantify small changes in brain ventricle volume in magnetic resonance (MR) images of a group of five patients treated with growth hormone replacement therapy and a control group of six volunteers is used.
Book ChapterDOI

Study of Connectivity in the Brain Using the Full Diffusion Tensor from MRI

TL;DR: This method involves solving the full diffusion equation over a finite element mesh derived from the MR data, and uses all the data in the diffusion tensor at each voxel to increase robustness and make intersubject comparisons easier.