Imperial College London

DrRolfHeckemann

Faculty of MedicineDepartment of Brain Sciences

Honorary Research Fellow
 
 
 
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Contact

 

+44 (0)20 8816 7653r.heckemann Website

 
 
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Location

 

Cyclotron buildingHammersmith Campus

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Summary

 

Publications

Publication Type
Year
to

102 results found

Butler C, van Erp W, Bhaduri A, Hammers A, Heckemann R, Zeman Aet al., 2013, Magnetic resonance volumetry reveals focal brain atrophy in transient epileptic amnesia, EPILEPSY & BEHAVIOR, Vol: 28, Pages: 363-369, ISSN: 1525-5050

Journal article

Ciumas C, Saignavongs M, Ilski F, Heckemann RA, Herbillon V, De Bellescize J, Panagiotakaki E, Hannoun S, Sappey-Marinier D, Ostrowsky-Coste K, Ryvlin Pet al., 2013, WHITE MATTER DEVELOPMENT IN CHILDREN WITH IDIOPATHIC LOCALIZATION-RELATED EPILEPSY, 30th International Epilepsy Congress, Publisher: WILEY-BLACKWELL, Pages: 237-237, ISSN: 0013-9580

Conference paper

Gousias IS, Hammers A, Counsell SJ, Srinivasan L, Rutherford MA, Heckemann RA, Hajnal JV, Rueckert D, Edwards ADet al., 2013, Magnetic Resonance Imaging of the Newborn Brain: Automatic Segmentation of Brain Images into 50 Anatomical Regions, PLOS ONE, Vol: 8, ISSN: 1932-6203

Journal article

Gray KR, Aljabar P, Heckemann R, Hammers A, Rueckert Det al., 2013, Manifold forests for multi-modality classification of Alzheimer's disease, Decision Forests for Computer Vision and Medical Image Analysis, Editors: Criminisi, Shotton, Publisher: Springer, ISBN: 9781447149286

The book concludes with a detailed discussion on the efficient implementation of decision forests. Topics and features: With a foreword by Prof. Yali Amit and Prof.

Book chapter

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

Journal article

Ledig C, Heckemann RA, Hammers A, Rueckert Det al., 2013, Improving whole-brain segmentations through incorporating regional image intensity statistics, Conference on Medical Imaging - Image Processing, Publisher: SPIE-INT SOC OPTICAL ENGINEERING, ISSN: 0277-786X

Conference paper

Squarcina L, Bertoldo A, Ham TE, Heckemann R, Sharp DJet al., 2012, A robust method for investigating thalamic white matter tracts after traumatic brain injury, NEUROIMAGE, Vol: 63, Pages: 779-788, ISSN: 1053-8119

Journal article

Keihaninejad S, Heckemann RA, Gousias IS, Hajnal JV, Duncan JS, Aljabar P, Rueckert D, Hammers Aet al., 2012, Classification and Lateralization of Temporal Lobe Epilepsies with and without Hippocampal Atrophy Based on Whole-Brain Automatic MRI Segmentation, PLOS ONE, Vol: 7, ISSN: 1932-6203

Journal article

Gray KR, Wolz R, Heckemann RA, Aljabar P, Hammers A, Rueckert Det al., 2012, Multi-region analysis of longitudinal FDG-PET for the classification of Alzheimer's disease, NEUROIMAGE, Vol: 60, Pages: 221-229, ISSN: 1053-8119

Journal article

Ledig C, Wolz R, Aljabar P, Lotjonen J, Heckemann RA, Hammers A, Rueckert Det al., 2012, MULTI-CLASS BRAIN SEGMENTATION USING ATLAS PROPAGATION AND EM-BASED REFINEMENT, 9th IEEE International Symposium on Biomedical Imaging (ISBI) - From Nano to Macro, Publisher: IEEE, Pages: 896-899

Conference paper

Ramlackhansingh AF, Brooks DJ, Greenwood RJ, Bose SK, Turkheimer FE, Kinnunen KM, Gentleman S, Heckemann RA, Gunanayagam K, Gelosa G, Sharp DJet al., 2011, Inflammation after Trauma: Microglial Activation and Traumatic Brain Injury, ANNALS OF NEUROLOGY, Vol: 70, Pages: 374-383, ISSN: 0364-5134

Journal article

Heckemann RA, Keihaninejad S, Aljabar P, Gray KR, Nielsen C, Rueckert D, Hajnal JV, Hammers Aet al., 2011, Automatic morphometry in Alzheimer's disease and mild cognitive impairment, NEUROIMAGE, Vol: 56, Pages: 2024-2037, ISSN: 1053-8119

Journal article

Gray KR, Aljabar P, Heckemann RA, Hammers A, Rueckert Det al., 2011, Random Forest-Based Manifold Learning for Classification of Imaging Data in Dementia, 2nd International Workshop on Machine Learning in Medical Imaging (MLMI 2011), Publisher: SPRINGER-VERLAG BERLIN, Pages: 159-+, ISSN: 0302-9743

Conference paper

Heckemann RA, Keihaninejad S, Aljabar P, Gray KR, Nielsen C, Rueckert D, Hajnal JV, Hammers Aet al., 2011, A REPOSITORY OF MR MORPHOMETRY DATA IN ALZHEIMER'S DISEASE AND MILD COGNITIVE IMPAIRMENT, 8th IEEE International Symposium on Biomedical Imaging (ISBI) - From Nano to Macro, Publisher: IEEE, Pages: 875-878, ISSN: 1945-7928

Conference paper

Gray KR, Wolz R, Keihaninejad S, Heckemann RA, Aljabar P, Hammers A, Rueckert Det al., 2011, REGIONAL ANALYSIS OF FDG-PET FOR USE IN THE CLASSIFICATION OF ALZHEIMER'S DISEASE, 8th IEEE International Symposium on Biomedical Imaging (ISBI) - From Nano to Macro, Publisher: IEEE, Pages: 1082-1085, ISSN: 1945-7928

Conference paper

Gousias IS, Hammers A, Heckemann RA, Counsell SJ, Dyet LE, Boardman JP, Edwards AD, Rueckert Det al., 2010, Atlas selection strategy for automatic segmentation of pediatric brain MRIs into 83 ROIs, Pages: 290-293

Registration algorithms can facilitate the automatic anatomical segmentation of pediatric brain MR data sets when segmentation priors (atlases) are in hand. Automatic segmentation can be achieved through label propagation and label fusion in target space. We investigated the performance of different age cohorts used as prior atlases for the segmentation of 13 MRIs of 1-year-olds. Thirty adults and 33 2-year-olds (including the 13 1-year olds, scanned a year later) served as priors for label propagation and fusion. In addition, we tested the accuracy of a single propagation step of the atlas of the same subject scanned at 2 years of age. Pediatric priors performed better than adult priors on visual inspection as well as manual validation of the caudate nucleus (Dice index=0.89±0.02 vs. 0.86±0.03). Corresponding single atlases at the age of 2 performed better than the fusion of 30 adult priors (83 ROIs / average Dice=0.87±0.05 vs. 0.84±0.07). © 2010 IEEE.

Conference paper

McGinnity CJ, Shidahara M, Keihaninejad S, Barros DAR, Gousias IS, Heckemann RA, Brooks DJ, Koepp MJ, Turkheimer FE, Hammers Aet al., 2010, Correction of [11C]diprenorphine PET data for the partial-volume effect: Quantification of opioid receptor binding following spontaneous epileptic seizures, 8th International Symposium on Functional Neuroreceptor Mapping of the Living Brain, Publisher: ACADEMIC PRESS INC ELSEVIER SCIENCE, Pages: S209-S209, ISSN: 1053-8119

Conference paper

Barros DAR, Heckemann RA, Rosso L, McGinnity CJ, Keihaninejad S, Gousias IS, Brooks DJ, Duncan JS, Koepp MJ, Turkheimer FE, Hammers Aet al., 2010, Investigating the reproducibility of the novel Alpha-5 GABAA receptor PET ligand [11C]Ro15 4513, 8th International Symposium on Functional Neuroreceptor Mapping of the Living Brain, Publisher: ACADEMIC PRESS INC ELSEVIER SCIENCE, Pages: S112-S112, ISSN: 1053-8119

Conference paper

Traynor C, Heckemann RA, Hammers A, O'Muircheartaigh J, Crum WR, Barker GJ, Richardson MPet al., 2010, Reproducibility of thalamic segmentation based on probabilistic tractography, NEUROIMAGE, Vol: 52, Pages: 69-85, ISSN: 1053-8119

Journal article

Wolz R, Heckemann RA, Aljabar P, Hajnal JV, Hammers A, Lotjonen J, Rueckert Det al., 2010, Measurement of hippocampal atrophy using 4D graph-cut segmentation: Application to ADNI, NEUROIMAGE, Vol: 52, Pages: 109-118, ISSN: 1053-8119

Journal article

Keihaninejad S, Heckemann RA, Gousias IS, Hajnal J, Duncan JS, Aljabar P, Rueckert D, Hammers Aet al., 2010, BRAIN-WIDE SURVEY OF ANATOMICAL STRUCTURES AS CLASSIFIERS IN TEMPORAL LOBE EPILEPSY USING AUTOMATIC SEGMENTATION AND STRUCTURE SELECTION, 9th European Congress on Epileptology

Poster

McGinnity CJ, Shidahara M, Keihaninejad S, Barros RDA, Gousias IS, Heckemann RA, Koepp MJ, Turkheimer FE, Hammers Aet al., 2010, QUANTIFICATION OF OPIOID RECEPTOR FOLLOWING SPONTANEOUS EPILEPTIC SEIZURES; CORRECTION OF [C-11]DIPRENORPHINE PET DATA FOR THE PARTIAL-VOLUME EFFECT, 9th European Congress on Epileptology, Publisher: WILEY-BLACKWELL, Pages: 90-90, ISSN: 0013-9580

Conference paper

Barros RDA, Heckemann RA, Keihaninejad S, McGinnity CJ, Gousias IS, Duncan JS, Koepp MJ, Brooks DJ, Hammers Aet al., 2010, TOWARD INVESTIGATING THE CAUSES OF MEMORY DIFFICULTIES IN TEMPORAL LOBE EPILEPSY: A STUDY USING THE NOVEL ALPHA5 GABA(A) RECEPTOR PET LIGAND [C-11]RO15 4513, 9th European Congress on Epileptology, Publisher: WILEY-BLACKWELL, Pages: 136-136, ISSN: 0013-9580

Conference paper

Heckemann RA, Keihaninejad S, Aljabar P, Rueckert D, Hajnal JV, Hammers Aet al., 2010, Improving intersubject image registration using tissue-class information benefits robustness and accuracy of multi-atlas based anatomical segmentation, NEUROIMAGE, Vol: 51, Pages: 221-227, ISSN: 1053-8119

Journal article

Keihaninejad S, Heckemann RA, Fagiolo G, Symms MR, Hajnal JV, Hammers Aet al., 2010, A robust method to estimate the intracranial volume across MRI field strengths (1.5T and 3T), NEUROIMAGE, Vol: 50, Pages: 1427-1437, ISSN: 1053-8119

Journal article

Keihaninejad S, Heckemann RA, Gousias IS, Hajnal JV, Duncan JS, Aljabar P, Rueckert D, Hammers Aet al., 2010, Automatic volumetry can reveal visually undetected disease features on brain MR images in temporal lobe epilepsy, ISBI 2010 (Seventh IEEE International Symposium on Biomedical Imaging)

Brain structural volumes can be used for automatically classifying subjects into categories like controls and patients. We aimed to automatically separate patients with temporal lobe epilepsy (TLE) with and without hippocampal atrophy on MRI, pTLE and nTLE, from controls, and determine the epileptogenic side. In the proposed framework 83 brain structure volumes are identified using multi-atlas segmentation. We then use structure selection using a divergence measure and classification based on structural volumes, as well as morphological similarities using SVM. A spectral analysis step is used to convert the pairwise measures of similarity between subjects into per-subject features. Up to 96% of pTLE patients were correctly separated from controls using 14 structural brain volumes. The classification method based on spectral analysis was 91% accurate at separating nTLE patients from controls. Right and left hippocampus were sufficient for the lateralization of the seizure focus in the pTLE group and achieved 100% accuracy.

Conference paper

Wolz R, Heckemann RA, Aljabar P, Hajnal JV, Hammers A, Lotjonen J, Rueckert Det al., 2010, MEASURING ATROPHY BY SIMULTANEOUS SEGMENTATION OF SERIAL MR IMAGES USING 4-D GRAPH-CUTS, 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Publisher: IEEE, Pages: 960-963, ISSN: 1945-7928

Conference paper

Hammers A, Heckemann RA, 2009, Construction and Use of Atlas Image Databases, Publisher: SPRINGER, Pages: S234-S234, ISSN: 1619-7070

Conference paper

Aljabar P, Heckemann RA, Hammers A, Hajnal JV, Rueckert Det al., 2009, Multi-atlas based segmentation of brain images: Atlas selection and its effect on accuracy, NEUROIMAGE, Vol: 46, Pages: 726-738, ISSN: 1053-8119

Journal article

Keihaninejad S, Heckemann RA, Gousias IS, Rueckert D, Aljabar P, Hajnal JV, Hammers Aet al., 2009, Automatic segmentation of brain MRIs and mapping neuroanatomy across the human lifespan, SPIE Medical Imaging

Conference paper

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