Chris Wright
London South Bank University
21 Papers
32 Citations
Chris Wright is an academic researcher from London South Bank University. The author has contributed to research in topics: Population & Medicine. The author has an hindex of 6, co-authored 20 publications. Previous affiliations of Chris Wright include University of Exeter & Sheffield Hallam University.
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Papers
•Proceedings Article
Linux Security Modules: General Security Support for the Linux Kernel
Chris Wright,Crispin Cowan,Stephen Smalley,James Morris,Greg Kroah-Hartman +4 more
- 05 Aug 2002
TL;DR: The design and implementation of LSM are presented and the challenges in providing a truly general solution that minimally impacts the Linux kernel are discussed.
501
Image interpretation performance: A longitudinal study from novice to professional
Chris Wright,Pauline Reeves +1 more
TL;DR: In this paper, the image interpretation performance of one cohort of student radiographers was measured upon enrolment from UCAS in the first week of university education and then again prior to graduation using RadBench (n ¼ 23).
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The academic radiography workforce: Age profile, succession planning and academic development.
TL;DR: There is vulnerability in the academic radiography workforce and higher education institutions need to invest in developing the academic workforce to maintain research and educational expertise, which is underpinned by master's and doctorate level qualifications.
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Hierarchical Cluster Analysis to Aid Diagnostic Image Data Visualization of MS and Other Medical Imaging Modalities.
TL;DR: This chapter discusses in detail the implementation of the HCS process, the implementation details of how the process is used for the presentation of multi-modal imaging data (MALDI and MRI) and how it is used as an interpretation aid for the interpretation of Multi-parametric Magnetic Resonance Imaging (mpMRI) of the Prostate.
Communication of medical images to diverse audiences using multimodal imaging
TL;DR: To create a model data set mouse fibrosarcoma tissue was visualised via magnetic resonance imaging, Matrix-Assisted Laser Desorption/Ionisation-Mass Spectrometry and histology, and sphingomyelin species could be used to identify regions of viable tumour in the MALDI-MSI data obtained.