Derek Magee is a lecturer in Computing at the University of Leeds with a research interest in medical image computing and machine learning, with a particular interest in Digital pathology image analysis. He has supervised 15 PhD students and numerous postdoctoral researchers since joining the university in 1997 and received funding from EPSRC, EU, CRUK, Wellcome Trust, Innovate Uk, LTH Charitable trust, and White Rose Health Innovation Partnership for projects as diverse as Interventional Ultrasound training systems, Cardiac image analysis, and developing digital pathology systems. He is currently involved in large projects relating to clinical adoption of digital pathology image analysis (NPIC - National Pathology Imaging Co-operative), and the use of image analysis in selecting patients for chemotherapy using digital pathology images. Additionally, he is supervisor of two PhD students for the Centre for Doctorial Training in AI in Medicine, as well as KTP associate in veterinary image analysis from video with company Vet-AI. In additional to his academic activities he is CTO and founder of HeteroGenius Limited (http://www.heterogenius.co.uk) a company producing software for management and analysis of digital pathology images. He has a strong record in commercialising academic research with software being licenced by ProZone limited for sports video analysis, and Cone beam-CT Quality Assurance system licenced by Modus QA.
Khan, Rajpoot, Treanor, Magee, A nonlinear mapping approach to stain normalization in digital histopathology images using image-specific colour deconvolution, IEEE Transactions on Biomedical Engineering, Vol. 61, Issue 6, pp1729-1738, 2014
Song, Treanor, Bulpitt, Wijayathunga, Roberts, Wilcox, Magee, Unsupervised content classification based nonrigid registration of differently stained histology images, IEEE Transactions on Biomedical Engineering 61 (1), 96-108, 2013
Roberts, Magee, Song, Brabazon, Shires, Crellin, Orsi, Quirke, Quirke, Treanor, Toward routine use of 3D histopathology as a research tool, The American journal of pathology, Vol. 180, Issue 5, pp1835-1842, 2012
Biglands, Magee, Sourbron, Plein, Greenwood, Comparison of the diagnostic performance of four quantitative myocardial perfusion estimation methods used in cardiac MR imaging: CE-MARC substudy, Radiology 275 (2), 393-402, 2015
Bernus, Radjenovic, Trew, LeGrice, Sands, Magee, et al., Comparison of diffusion tensor imaging by cardiovascular magnetic resonance and gadolinium enhanced 3D image intensity approaches to investigation of structural anisotropy in explanted rat hearts, Journal of Cardiovascular Magnetic Resonance 17 (1), 1-27, 2015
Sykes, Brettle, Magee, Thwaites, Measurement of cone beam CT coincidence with megavoltage isocentre and image sharpness using the QUASARâ¢ Penta-Guide phantom, Physics in Medicine & Biology 53 (19), 7263, 2008.