Imperial College London

ProfessorDanielRueckert

Faculty of EngineeringDepartment of Computing

Professor of Visual Information Processing
 
 
 
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Contact

 

+44 (0)20 7594 8333d.rueckert Website

 
 
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Location

 

568Huxley BuildingSouth Kensington Campus

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Summary

 

Summary

Biography

Daniel Rueckert joined the Department of Computing as a lecturer in 1999 and became senior lecturer in 2003. Since 2005 he is Professor of Visual Information Processing and heads the Biomedical Image Analysis group. He received a Diploma in Computer Science (equiv to M.Sc.) from the Technical University Berlin and a Ph.D. in Computer Science from Imperial College London. Before moving to Imperial College, he has worked as a post-doctoral research fellow in the Division of Radiological Sciences and Medical Engineering, King's College London where he has worked on the development of non-rigid registration algorithms for the compensation of tissue motion and deformation. The developed registration techniques have been successfully used for the non-rigid registration of various anatomical structures, including in the breast, liver, heart and brain and are currently commercialized by IXICO, an Imperial College spin-out company. During his doctoral and post-doctoral research he has published more than 300 journal and conference articles. Professor Rueckert is an associate editor of IEEE Transactions on Medical Imaging, a member of the editorial board of Medical Image Analysis, Image & Vision Computing and a referee for a number of international medical imaging journals and conferences. He has served as a member of organising and programme committees at numerous conferences, e.g. he has been General Co-chair of MMBIA 2006 and FIMH 2013 as well as Programme Co-Chair of MICCAI 2009, ISBI 2012 and WBIR 2012In 2014, he has been elected as a Fellow of the MICCAI society and in 2015 he was elected as a Fellow of the Royal Academy of Engineering.

 

Further information

Please look at my personal webpage.

Selected Publications

Journal Articles

Bowles, Qin C, Guerrero R, et al., 2017, Brain Lesion Segmentation through Image Synthesis and Outlier Detection, Neuroimage: Clinical, Vol:16, ISSN:2213-1582, Pages:643-658

Wolz R, Chu C, Misawa K, et al., 2013, Automated Abdominal Multi-Organ Segmentation With Subject-Specific Atlas Generation, IEEE Transactions on Medical Imaging, Vol:32, ISSN:0278-0062, Pages:1723-1730

Shi W, Jantsch M, Aljabar P, et al., 2013, Temporal sparse free-form deformations, Medical Image Analysis

Gray KR, Aljabar P, Heckemann RA, et al., 2013, Random forest-based similarity measures for multi-modal classification of Alzheimer's disease, Neuroimage, Vol:65, ISSN:1053-8119, Pages:167-175

Aljabar P, Wolz R, Srinivasan L, et al., 2011, A Combined Manifold Learning Analysis of Shape and Appearance to Characterize Neonatal Brain Development, IEEE Transactions on Medical Imaging, Vol:30, ISSN:0278-0062, Pages:2072-2086

Lotjonen JMP, Wolz R, Koikkalainen JR, et al., 2010, Fast and robust multi-atlas segmentation of brain magnetic resonance images, Neuroimage, Vol:49, ISSN:1053-8119, Pages:2352-2365

Wolz R, Aljabar P, Hajnal JV, et al., 2010, LEAP: Learning embeddings for atlas propagation, Neuroimage, Vol:49, ISSN:1053-8119, Pages:1316-1325

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