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

114 results found

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

Heckemann RA, Hammers A, Aljabar P, Rueckert D, Hajnal JVet al., 2009, THE MIRROR METHOD OF ASSESSING SEGMENTATION QUALITY IN ATLAS LABEL PROPAGATION, IEEE International Symposium on Biomedical Imaging - From Nano to Macro, Publisher: IEEE, Pages: 1194-+

Conference paper

Wolz R, Aljabar P, Rueckert D, Heckemann RA, Hammers Aet al., 2009, SEGMENTATION OF SUBCORTICAL STRUCTURES AND THE HIPPOCAMPUS IN BRAIN MRI USING GRAPH-CUTS AND SUBJECT-SPECIFIC A-PRIORI INFORMATION, IEEE International Symposium on Biomedical Imaging - From Nano to Macro, Publisher: IEEE, Pages: 470-+

Conference paper

Heckemann RA, Hammers A, Rueckert D, Aviv RI, Harvey CJ, Hajnal JVet al., 2008, Automatic volumetry on MR brain images can support diagnostic decision making., BMC Med Imaging, Vol: 8

BACKGROUND: Diagnostic decisions in clinical imaging currently rely almost exclusively on visual image interpretation. This can lead to uncertainty, for example in dementia disease, where some of the changes resemble those of normal ageing. We hypothesized that extracting volumetric data from patients' MR brain images, relating them to reference data and presenting the results as a colour overlay on the grey scale data would aid diagnostic readers in classifying dementia disease versus normal ageing. METHODS: A proof-of-concept forced-choice reader study was designed using MR brain images from 36 subjects. Images were segmented into 43 regions using an automatic atlas registration-based label propagation procedure. Seven subjects had clinically probable AD, the remaining 29 of a similar age range were used as controls. Seven of the control subject data sets were selected at random to be presented along with the seven AD datasets to two readers, who were blinded to all clinical and demographic information except age and gender. Readers were asked to review the grey scale MR images and to record their choice of diagnosis (AD or non-AD) along with their confidence in this decision. Afterwards, readers were given the option to switch on a false-colour overlay representing the relative size of the segmented structures. Colorization was based on the size rank of the test subject when compared with a reference group consisting of the 22 control subjects who were not used as review subjects. The readers were then asked to record whether and how the additional information had an impact on their diagnostic confidence. RESULTS: The size rank colour overlays were useful in 18 of 28 diagnoses, as determined by their impact on readers' diagnostic confidence. A not useful result was found in 6 of 28 cases. The impact of the additional information on diagnostic confidence was significant (p < 0.02). CONCLUSION: Volumetric anatomical information extracted from brain images using

Journal article

Gousias IS, Rueckert D, Heckemann RA, Dyet LE, Boardman JP, Edwards AD, Hammers Aet al., 2008, Automatic segmentation of brain MRIs of 2-year-olds into 83 regions of interest, NEUROIMAGE, Vol: 40, Pages: 672-684, ISSN: 1053-8119

Journal article

Hammers A, Panagoda P, Heckemann RA, Kelsch W, Turkheimer FE, Brooks DJ, Duncan JS, Koepp MJet al., 2008, [(11)C] Flumazenil PET in temporal lobe epilepsy: do we need an arterial input function or kinetic modeling?, JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM, Vol: 28, Pages: 207-216, ISSN: 0271-678X

Journal article

Gousias IS, Rueckert D, Heckemann RA, Dyet LE, Boardman JP, Edwards AD, Hammers Aet al., 2007, An automatic segmentation of brain MRIs of 2-year-olds into 83 regions of interest

Poster

Hammers A, Panagoda P, Heckemann RA, Kelsch W, Turkheimer FE, Brooks DJ, Duncan JS, Koepp MJet al., 2007, Quantification strategies for [11C]flumazenil pet in temporal lobe epilepsy: Do they matter?, 61st Annual Meeting of the American-Epilepsy-Society, Publisher: WILEY-BLACKWELL, Pages: 162-163, ISSN: 0013-9580

Conference paper

Hammers A, Heckemann R, Koepp MJ, Duncan JS, Hajnal JV, Rueckert D, Alabar Pet al., 2007, Automatic detection and quantification of hippocampal atrophy on MRI in temporal lobe epilepsy: A proof-of-principle study, NEUROIMAGE, Vol: 36, Pages: 38-47, ISSN: 1053-8119

Journal article

Ketelsen D, Schroedl F, Knickenberg I, Heckemann RA, Hothorn T, Neuhuber WL, Bautz WA, Grunewald Met al., 2007, Modes of information delivery in radiologic anatomy education: Impact on student performance, ACADEMIC RADIOLOGY, Vol: 14, Pages: 93-99, ISSN: 1076-6332

Journal article

Aljabar P, Heckeman R, Hammers A, Hajnal JV, Rueckert Det al., 2007, Classifier selection strategies for label fusion using large atlas databases, 10th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2007), Publisher: SPRINGER-VERLAG NEW YORK, MS INGRID CUNNINGHAM, 175 FIFTH AVE, NEW YORK, NY 10010 USA, Pages: 523-531, ISSN: 0302-9743

Conference paper

Rueckert D, Aljabar P, Heckemann R, Hajnal J, Hammers Aet al., 2006, Diffeomorphic Registration using B-Splines, 9th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2006), Publisher: Springer

Conference paper

Heckemann R, Hajnal J, Aljabar P, Rueckert D, Hammers Aet al., 2006, Multiclassifier fusion in human brain MR segmentation: modelling convergence, 9th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2006), Publisher: Springer

Conference paper

Grunewald M, Ketelsen D, Heckemann RA, Zenk J, Schick C, Bison B, Anders D, Knickenberg L, Wagner M, Neuhuber W, Bickel A, Bautz W, Greess Het al., 2006, Www.tnt-radiology.de: Teach and be taught radiology: Implementation of a web-based training program based on user preferences as determined by survery, ACADEMIC RADIOLOGY, Vol: 13, Pages: 461-468, ISSN: 1076-6332

Journal article

Heckemann R, Hajnal J, Aljabar P, Rueckert D, Hammers Aet al., 2006, Automatic anatomical brain MRI segmentation combining label propagation and decision fusion, NeuroImage

Journal article

Sneller B, Dresner MA, Heckemann RA, Hajnal JV, Hill DGet al., 2005, [P-106]: Serial MR neuroimaging: Comparison at 3T and 1.5T, Alzheimer's & Dementia, Vol: 1, Pages: S42-S42, ISSN: 1552-5260

Journal article

Wagner M, Heckemann RA, Nomayr A, Greess H, Bautz WA, Grunewald Met al., 2005, COMPARE/Radiology, an interactive Web-based radiology teaching program: Evaluation of user response, ACADEMIC RADIOLOGY, Vol: 12, Pages: 752-760, ISSN: 1076-6332

Journal article

Heckemann RA, Hajnal JV, Rueckert D, Hill DLG, Hammers Aet al., 2005, Propagating labels of the human brain based on non-rigid MR image registration: an evaluation, Medical Imaging 2005 Conference, Publisher: SPIE-INT SOC OPTICAL ENGINEERING, Pages: 1864-1871, ISSN: 0277-786X

Conference paper

Ren JS, Sneller B, Rueckert D, Hajnal J, Heckerman R, Smith S, Vickers J, Hill Det al., 2005, A comparison of the tissue classification and the segmentation propagation techniques in MRI brain image segmentation, Medical Imaging 2005 Conference, Publisher: SPIE-INT SOC OPTICAL ENGINEERING, Pages: 1682-1691, ISSN: 0277-786X

Conference paper

Grunewald M, Heckemann RA, Wagner M, Bautz WA, Greess Het al., 2004, ELERA: A WWW application for evaluating and developing radiologic skills and knowledge, ACADEMIC RADIOLOGY, Vol: 11, Pages: 1381-1388, ISSN: 1076-6332

Journal article

Leung KK, Heckemann RA, Saeed N, Brooks KJ, Buckton JB, Changani K, Reid DG, Rueckert D, Hajnal JV, Holden M, Hill DLGet al., 2004, Analysis of serial MR images of joints, 2nd IEEE International Symposium on Biomedical Imaging, Publisher: IEEE, Pages: 221-224

Conference paper

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