Rolf A. Heckemann

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Alexander HammersSchool of Biomedical Engineering and Imaging Sciences, King's College LondonVerified email at kcl.ac.uk
Daniel RueckertTechnical University of Munich and Imperial College LondonVerified email at tum.de
Paul AljabarPerspectum DiagnosticsVerified email at imperial.ac.uk
Jo HajnalProfessor of Imaging Science, Kings College LondonVerified email at kcl.ac.uk
Robert Eckersley(until 2019) Senior Lecturer, King's College LondonVerified email at kcl.ac.uk
Federico TurkheimerProfessor of Neuroimaging, King's College LondonVerified email at kcl.ac.uk
David J BrooksProfessor of PET Clinical Science Newcastle University UKVerified email at newcastle.ac.uk
Alzheimer's Disease Neuroimaging Ini...Verified email at njit.edu
Robin WolzResearch Fellow, Imperial College London. Chief Scientific Officer, IXICO.Verified email at imperial.ac.uk
Christian LedigProfessor of Explainable Machine Learning, University of BambergVerified email at uni-bamberg.de
KoeppUCLVerified email at ucl.ac.uk
David J SharpDirector Care Research & Technology Centre, UK Dementia Research Institute, Imperial College LondonVerified email at imperial.ac.uk
Jyrki LötjönenCombinostics LtdVerified email at combinostics.com
Costes NicolasCERMEP, MNI, Mc GillVerified email at cermep.fr
Colm J McGinnityKing's College LondonVerified email at kcl.ac.uk
A David EdwardsProfessor of Paediatrics and Neonatal Medicine, King's College LondonVerified email at kcl.ac.uk
Steve GentlemanImperial College LondonVerified email at imperial.ac.uk
Professor James P BoardmanUniversity of EdinburghVerified email at ed.ac.uk
Mattia VeroneseAssociate professor in Biomedical Engineering at University of PaduaVerified email at unipd.it
Derek HillCEO, Panoramic Digital HealthVerified email at ucl.ac.uk

Rolf A. Heckemann

Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy

Verified email at gu.se

Medical image analysis computational anatomy


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Automatic anatomical brain MRI segmentation combining label propagation and decision fusion RA Heckemann, JV Hajnal, P Aljabar, D Rueckert, A Hammers NeuroImage 33 (1), 115-126, 2006	1121	2006
Multi-atlas based segmentation of brain images: atlas selection and its effect on accuracy P Aljabar, RA Heckemann, A Hammers, JV Hajnal, D Rueckert Neuroimage 46 (3), 726-738, 2009	1110	2009
Inflammation after trauma: microglial activation and traumatic brain injury AF Ramlackhansingh, DJ Brooks, RJ Greenwood, SK Bose, ... Annals of neurology 70 (3), 374-383, 2011	981	2011
Random forest-based similarity measures for multi-modal classification of Alzheimer's disease KR Gray, P Aljabar, RA Heckemann, A Hammers, D Rueckert, ... NeuroImage 65, 167-175, 2013	493	2013
Diffeomorphic registration using B-splines D Rueckert, P Aljabar, RA Heckemann, JV Hajnal, A Hammers Medical Image Computing and Computer-Assisted Intervention–MICCAI 2006: 9th …, 2006	408	2006
Automatic segmentation of brain MRIs of 2-year-olds into 83 regions of interest IS Gousias, D Rueckert, RA Heckemann, LE Dyet, JP Boardman, ... Neuroimage 40 (2), 672-684, 2008	372	2008
Improving intersubject image registration using tissue-class information benefits robustness and accuracy of multi-atlas based anatomical segmentation RA Heckemann, S Keihaninejad, P Aljabar, D Rueckert, JV Hajnal, ... Neuroimage 51 (1), 221-227, 2010	229	2010
Pulse-inversion mode imaging of liver specific microbubbles: improved detection of subcentimetre metastases CJ Harvey, MJK Blomley, RJ Eckersley, RA Heckemann, J Butler-Barnes, ... The Lancet 355 (9206), 807-808, 2000	209	2000
Multi-region analysis of longitudinal FDG-PET for the classification of Alzheimer's disease KR Gray, R Wolz, RA Heckemann, P Aljabar, A Hammers, D Rueckert, ... NeuroImage 60 (1), 221-229, 2012	196	2012
Robust whole-brain segmentation: application to traumatic brain injury C Ledig, RA Heckemann, A Hammers, JC Lopez, VFJ Newcombe, ... Medical image analysis 21 (1), 40-58, 2015	192	2015
Liver microbubble transit time compared with histology and Child-Pugh score in diffuse liver disease: a cross sectional study MJK Blomley, AKP Lim, CJ Harvey, N Patel, RJ Eckersley, R Basilico, ... Gut 52 (8), 1188-1193, 2003	171	2003
Automatic morphometry in Alzheimer's disease and mild cognitive impairment RA Heckemann, S Keihaninejad, P Aljabar, KR Gray, C Nielsen, ... Neuroimage 56 (4), 2024-2037, 2011	156	2011
Measurement of hippocampal atrophy using 4D graph-cut segmentation: application to ADNI R Wolz, RA Heckemann, P Aljabar, JV Hajnal, A Hammers, J Lötjönen, ... NeuroImage 52 (1), 109-118, 2010	154	2010
Structural brain imaging in Alzheimer’s disease and mild cognitive impairment: biomarker analysis and shared morphometry database C Ledig, A Schuh, R Guerrero, RA Heckemann, D Rueckert Scientific reports 8 (1), 11258, 2018	148	2018
Amyloid pathology and axonal injury after brain trauma G Scott, AF Ramlackhansingh, P Edison, P Hellyer, J Cole, M Veronese, ... Neurology 86 (9), 821-828, 2016	146	2016
Hepatic malignancies: improved detection with pulse-inversion US in late phase of enhancement with SH U 508A—early experience CJ Harvey, MJK Blomley, RJ Eckersley, DO Cosgrove, N Patel, ... Radiology 216 (3), 903-908, 2000	141	2000
Do different types of liver lesions differ in their uptake of the microbubble contrast agent SH U 508A in the late liver phase? Early experience MJK Blomley, PS Sidhu, DO Cosgrove, T Albrecht, CJ Harvey, ... Radiology 220 (3), 661-667, 2001	139	2001
Stimulated acoustic emission to image a late liver and spleen-specific phase of Levovist® in normal volunteers and patients with and without liver disease MJK Blomley, T Albrecht, DO Cosgrove, RJ Eckersley, J Butler-Barnes, ... Ultrasound in medicine & biology 25 (9), 1341-1352, 1999	136	1999
A robust method to estimate the intracranial volume across MRI field strengths (1.5 T and 3T) S Keihaninejad, RA Heckemann, G Fagiolo, MR Symms, JV Hajnal, ... Neuroimage 50 (4), 1427-1437, 2010	133	2010
Macroanatomy and 3D probabilistic atlas of the human insula I Faillenot, RA Heckemann, M Frot, A Hammers NeuroImage 150, 88-98, 2017	121	2017

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