Rolf A Heckemann

Summary

Affiliation: Imperial College
Country: UK

Publications

  1. ncbi Improving intersubject image registration using tissue-class information benefits robustness and accuracy of multi-atlas based anatomical segmentation
    Rolf A Heckemann
    Division of Neuroscience and Mental Health, Faculty of Medicine, Department of Computing, Imperial College, London, UK
    Neuroimage 51:221-7. 2010
  2. pmc Automatic volumetry on MR brain images can support diagnostic decision making
    Rolf A Heckemann
    Division of Neurosciences and Mental Health, Imperial College London, Hammersmith Campus, Du Cane Road, London, UK
    BMC Med Imaging 8:9. 2008
  3. pmc Automatic morphometry in Alzheimer's disease and mild cognitive impairment
    Rolf A Heckemann
    The Neurodis Foundation Fondation Neurodis, Lyon, France
    Neuroimage 56:2024-37. 2011
  4. ncbi Groupwise combined segmentation and registration for atlas construction
    Kanwal K Bhatia
    Visual Information Processing, Department of Computing, Imperial College London
    Med Image Comput Comput Assist Interv 10:532-40. 2007
  5. ncbi Analysis of serial magnetic resonance images of mouse brains using image registration
    Satheesh Maheswaran
    Department of Computing, South Kensington Campus, Imperial College, London, UK address
    Neuroimage 44:692-700. 2009
  6. ncbi Diffusion tensor imaging (DTI) of the brain in moving subjects: application to in-utero fetal and ex-utero studies
    Shuzhou Jiang
    Imaging Science Department, MRC Clinical Sciences Centre, Imperial College Hammersmith Hospital Campus, London, UK
    Magn Reson Med 62:645-55. 2009
  7. ncbi Longitudinal cortical registration for developing neonates
    Hui Xue
    Imaging Sciences Department, Imperial College, London, Du Cane Road, W12 0NN, UK
    Med Image Comput Comput Assist Interv 10:127-35. 2007
  8. ncbi Measurement of hippocampal atrophy using 4D graph-cut segmentation: application to ADNI
    Robin Wolz
    Department of Computing, Imperial College London, London, UK
    Neuroimage 52:109-18. 2010
  9. ncbi Identifying population differences in whole-brain structural networks: a machine learning approach
    Emma C Robinson
    Department of Computing, Imperial College London, London, UK
    Neuroimage 50:910-9. 2010
  10. ncbi Segmentation of brain MRI in young children
    Maria Murgasova
    Visual Information Processing Group, Department of Computing, Imperial College, London, UK
    Acad Radiol 14:1350-66. 2007

Detail Information

Publications60

  1. ncbi Improving intersubject image registration using tissue-class information benefits robustness and accuracy of multi-atlas based anatomical segmentation
    Rolf A Heckemann
    Division of Neuroscience and Mental Health, Faculty of Medicine, Department of Computing, Imperial College, London, UK
    Neuroimage 51:221-7. 2010
    ....
  2. pmc Automatic volumetry on MR brain images can support diagnostic decision making
    Rolf A Heckemann
    Division of Neurosciences and Mental Health, Imperial College London, Hammersmith Campus, Du Cane Road, London, UK
    BMC Med Imaging 8:9. 2008
    ....
  3. pmc Automatic morphometry in Alzheimer's disease and mild cognitive impairment
    Rolf A Heckemann
    The Neurodis Foundation Fondation Neurodis, Lyon, France
    Neuroimage 56:2024-37. 2011
    ..An automatically derived white-matter hypointensities index was found to be a suitable means of quantifying white-matter disease. This repository of segmentations is a potentially valuable resource to researchers working with ADNI data...
  4. ncbi Groupwise combined segmentation and registration for atlas construction
    Kanwal K Bhatia
    Visual Information Processing, Department of Computing, Imperial College London
    Med Image Comput Comput Assist Interv 10:532-40. 2007
    ..These have been used to quantify the growth of tissues occurring between these ages...
  5. ncbi Analysis of serial magnetic resonance images of mouse brains using image registration
    Satheesh Maheswaran
    Department of Computing, South Kensington Campus, Imperial College, London, UK address
    Neuroimage 44:692-700. 2009
    ..In contrast to this, the deformation-based approach can detect statistically significant differences in highly localized areas...
  6. ncbi Diffusion tensor imaging (DTI) of the brain in moving subjects: application to in-utero fetal and ex-utero studies
    Shuzhou Jiang
    Imaging Science Department, MRC Clinical Sciences Centre, Imperial College Hammersmith Hospital Campus, London, UK
    Magn Reson Med 62:645-55. 2009
    ..Results from normal fetal brains were found to be consistent with published data from premature infants of similar gestational age...
  7. ncbi Longitudinal cortical registration for developing neonates
    Hui Xue
    Imaging Sciences Department, Imperial College, London, Du Cane Road, W12 0NN, UK
    Med Image Comput Comput Assist Interv 10:127-35. 2007
    ..Each infant has been scanned at three different time points. Quantitative results are obtained by propagating sulci across multiple gestational ages and computing the overlap ratios with manually established ground-truth...
  8. ncbi Measurement of hippocampal atrophy using 4D graph-cut segmentation: application to ADNI
    Robin Wolz
    Department of Computing, Imperial College London, London, UK
    Neuroimage 52:109-18. 2010
    ..Power analysis shows that 67 and 206 subjects are needed for the AD and MCI groups respectively to detect a 25% change in volume loss with 80% power and 5% significance...
  9. ncbi Identifying population differences in whole-brain structural networks: a machine learning approach
    Emma C Robinson
    Department of Computing, Imperial College London, London, UK
    Neuroimage 50:910-9. 2010
    ..We show that subjects can be classified successfully (with 87.46% accuracy) and that the features extracted from the discriminant analysis agree with current consensus on the neurological impact of ageing...
  10. ncbi Segmentation of brain MRI in young children
    Maria Murgasova
    Visual Information Processing Group, Department of Computing, Imperial College, London, UK
    Acad Radiol 14:1350-66. 2007
    ..This article deals with an automatic tissue segmentation of brain magnetic resonance imaging (MRI) in young children...
  11. ncbi MRI of moving subjects using multislice snapshot images with volume reconstruction (SVR): application to fetal, neonatal, and adult brain studies
    Shuzhou Jiang
    Imaging Sciences Department, MRC Clinical Sciences Centre, Hammersmith Hospital, Imperial College London, UK
    IEEE Trans Med Imaging 26:967-80. 2007
    ..Fine structure of the in-utero fetal brain is clearly revealed for the first time and substantial SNR improvement is realized by having many individually acquired slices contribute to each voxel in the reconstructed image...
  12. ncbi Multiclassifier fusion in human brain MR segmentation: modelling convergence
    Rolf A Heckemann
    Imaging Sciences Department, MRC Clinical Sciences Centre, Imperial College at Hammersmith Hospital Campus, London, UK
    Med Image Comput Comput Assist Interv 9:815-22. 2006
    ..Fit parameters of this model are potential indicators of the quality of a given label propagation method or the consistency of the input segmentations used...
  13. ncbi Multivariate statistical analysis of whole brain structural networks obtained using probabilistic tractography
    Emma C Robinson
    Department of Computing, Imperial College, London SW7 2BZ, UK
    Med Image Comput Comput Assist Interv 11:486-93. 2008
    ..Classification performance was tested using a leave-one-out approach and the mean accuracy obtained was 85.4%...
  14. ncbi Early growth in brain volume is preserved in the majority of preterm infants
    James P Boardman
    Imaging Sciences Department, Medical Research Council Clinical Sciences Centre, Imperial College London, Hammersmith Hospital, London, United Kingdom
    Ann Neurol 62:185-92. 2007
    ..This study addresses the question: Is reduced global brain growth in the neonatal period inevitable after premature birth, or is it associated with specific medical risk factors?..
  15. ncbi Automatic cortical segmentation in the developing brain
    Hui Xue
    Imaging Sciences Department, Imperial College, London, Du Cane Road, UK
    Inf Process Med Imaging 20:257-69. 2007
    ..Quantitative comparison to the manual segmentation demonstrates good performance of the method (mean Dice similarity: 0.758 +/- 0.037 for GM and 0.794 +/- 0.078 for WM)...
  16. ncbi In-utero three dimension high resolution fetal brain diffusion tensor imaging
    Shuzhou Jiang
    Imaging Sciences Department, MRC Clinical Sciences Centre, Hammersmith Hospital, Imperial College London, London, United Kingdom
    Med Image Comput Comput Assist Interv 10:18-26. 2007
    ..The method has been tested successful on eight fetuses and has been validated on adults imaged at 1.5T...
  17. ncbi Analysis of 3-D myocardial motion in tagged MR images using nonrigid image registration
    Raghavendra Chandrashekara
    Visual Information Processing Group, Department of Computing, Imperial College, 180 Queen s Gate, London SW7 2AZ, U K
    IEEE Trans Med Imaging 23:1245-50. 2004
    ..We use both short-axis and long-axis images of the heart to estimate the full four-dimensional motion field within the myocardium. We also present validation results from data acquired from twelve volunteers...
  18. doi A dynamic 4D probabilistic atlas of the developing brain
    Maria Kuklisova-Murgasova
    Department of Computing, Imperial College London, London, UK
    Neuroimage 54:2750-63. 2011
    ..The atlas is publicly available at www.brain-development.org...
  19. pmc LEAP: learning embeddings for atlas propagation
    Robin Wolz
    Visual Information Processing Group, Department of Computing, Imperial College London, 180 Queen s Gate, London, SW7 2AZ, UK
    Neuroimage 49:1316-25. 2010
    ..with a greater difference between atlas and image. For the segmentation of the hippocampus on 182 images for which a manual segmentation is available, we achieved an average overlap (Dice coefficient) of 0.85 with the manual reference...
  20. ncbi Automatic segmentation and reconstruction of the cortex from neonatal MRI
    Hui Xue
    Robert Steiner MR Unit, Imaging Sciences Department, Hammersmith Campus, Imperial College, Du Cane Road, W12 0NN, London, UK
    Neuroimage 38:461-77. 2007
    ....
  21. ncbi Similarity metrics for groupwise non-rigid registration
    Kanwal K Bhatia
    Visual Information Processing, Department of Computing, Imperial College London
    Med Image Comput Comput Assist Interv 10:544-52. 2007
    ..The described groupwise metrics are quantitatively evaluated on simulated and 3D MR datasets, and their performance compared to equivalent pairwise registration...
  22. ncbi Simultaneous fine and coarse diffeomorphic registration: application to atrophy measurement in Alzheimer's disease
    Laurent Risser
    Institute for Mathematical Science, Imperial College London, 53 Prince s Gate, SW7 2PG London, UK
    Med Image Comput Comput Assist Interv 13:610-7. 2010
    ..More importantly, the results also demonstrate its ability to measure shape variations at several scales simultaneously while keeping the desirable properties of LDDMM. This opens new perspectives for clinical applications...
  23. pmc Classification and lateralization of temporal lobe epilepsies with and without hippocampal atrophy based on whole-brain automatic MRI segmentation
    Shiva Keihaninejad
    Division of Experimental Medicine, Centre for Neuroscience, Faculty of Medicine, Imperial College London, United Kingdom
    PLoS ONE 7:e33096. 2012
    ..Such morphometric image features may serve as classification and lateralization criteria. The technique also detects unsuspected distinguishing features like the substantia nigra, warranting further study...
  24. ncbi Diffeomorphic registration using B-splines
    Daniel Rueckert
    Department of Computing, Imperial College London, UK
    Med Image Comput Comput Assist Interv 9:702-9. 2006
    ..The results show that the proposed algorithm generates diffeomorphic transformations while providing similar levels of performance as the existing FFD registration algorithm in terms of registration accuracy...
  25. pmc A robust method to estimate the intracranial volume across MRI field strengths (1.5T and 3T)
    Shiva Keihaninejad
    Division of Neuroscience and Mental Health, MRC Clinical Sciences Centre, Imperial College London, London, UK
    Neuroimage 50:1427-37. 2010
    ..RBM achieved the best combination of precision and reliability in a group of healthy subjects, a group of patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI) and can be used as a common normalization framework...
  26. ncbi Spectral clustering as a diagnostic tool in cross-sectional MR studies: an application to mild dementia
    Paul Aljabar
    Department of Computing, Imperial College London, UK
    Med Image Comput Comput Assist Interv 11:442-9. 2008
    ..The results indicate that unsupervised classification following a spectral analysis of label overlaps performs very well, outperforming classifiers that use volumes alone...
  27. ncbi Spatio-temporal free-form registration of cardiac MR image sequences
    Dimitrios Perperidis
    Visual Information Processing Group, Department of Computing, Imperial College London, 180 Queens Gate, London SW7 2BZ, United Kingdom
    Med Image Anal 9:441-56. 2005
    ..We demonstrate the use of the method for the construction of a probabilistic MR cardiac atlas representing the anatomy and function of a healthy heart...
  28. ncbi Automatic quantification of changes in bone in serial MR images of joints
    Kelvin K Leung
    University College London, London, UK
    IEEE Trans Med Imaging 25:1617-26. 2006
    ..But the global bone volume was found to be fluctuating over time. Finally, we compare our findings with histology of the subjects and the manual segmentation of bone lesions...
  29. doi Construction of a consistent high-definition spatio-temporal atlas of the developing brain using adaptive kernel regression
    Ahmed Serag
    Biomedical Image Analysis BioMedIA Group, Department of Computing, Imperial College London, and Centre for the Developing Brain, Hammersmith Hospital, London, UK
    Neuroimage 59:2255-65. 2012
    ..Also, the resulting 4D atlas can serve as a good representative of the population of interest as it reflects both global and local changes. The atlas is publicly available at www.brain-development.org...
  30. ncbi Construction of a 4D statistical atlas of the cardiac anatomy and its use in classification
    Dimitrios Perperidis
    Visual Information Processing Group, Department of Computing, Imperial College, London, 180 Queen s Gate, London SW7 2BZ, United Kingdom
    Med Image Comput Comput Assist Interv 8:402-10. 2005
    ..We show how the resulting statistical atlas can be used to differentiate between cardiac image sequences from patients with hypertrophic cardiomyopathy and normal subjects...
  31. ncbi Test-retest reproducibility of cannabinoid-receptor type 1 availability quantified with the PET ligand [¹¹C]MePPEP
    Daniela A Riaño Barros
    Centre for Neuroscience, Department of Medicine, Imperial College London, London, UK MRC Clinical Sciences Centre Hammersmith Hospital, London, UK
    Neuroimage 97:151-62. 2014
    ..The objective of this study was to quantify the test-retest reproducibility of measures of the PET ligand [(11)C]MePPEP in order to assess the stability of CB1-receptor quantification in humans in vivo...
  32. doi Quantification of opioid receptor availability following spontaneous epileptic seizures: correction of [11C]diprenorphine PET data for the partial-volume effect
    Colm J McGinnity
    Centre for Neuroscience, Department of Medicine, Imperial College London, London W12 0NN, UK
    Neuroimage 79:72-80. 2013
    ..Denoising, resolution recovery and precise anatomical segmentation can extract valuable information from PET studies that would be missed with conventional post-processing procedures...
  33. ncbi Construction of a statistical model for cardiac motion analysis using nonrigid image registration
    Raghavendra Chandrashekara
    Visual Information Processing Group, Department of Computing, Imperial College of Science, Technology, and Medicine, 180 Queen s Gate, London SW7 2BZ, UK
    Inf Process Med Imaging 18:599-610. 2003
    ..The modes of variation obtained were then used to parametrize the free-form deformations and build our statistical model. The results of using our model to track the motion of the heart in normal volunteers are also presented...
  34. pmc Random forest-based similarity measures for multi-modal classification of Alzheimer's disease
    Katherine R Gray
    Biomedical Image Analysis Group, Department of Computing, Imperial College London, UK
    Neuroimage 65:167-75. 2013
    ..Random forest classifiers extend naturally to multi-class problems, and the framework described here could be applied to distinguish between multiple patient groups in the future...
  35. pmc Multi-region analysis of longitudinal FDG-PET for the classification of Alzheimer's disease
    Katherine R Gray
    Biomedical Image Analysis Group, Department of Computing, Imperial College London, UK
    Neuroimage 60:221-9. 2012
    ..This finding may be usefully applied in the diagnosis of Alzheimer's disease, predicting disease course in individuals with mild cognitive impairment, and in the selection of participants for clinical trials...
  36. ncbi A probabilistic framework to infer brain functional connectivity from anatomical connections
    Fani Deligianni
    Department of Computing, Imperial College London, UK
    Inf Process Med Imaging 22:296-307. 2011
    ..Our results show that functional connectivity can be explained by anatomical connectivity on a rigorous statistical basis, and that a proper model of functional connectivity is essential to assess this link...
  37. ncbi An optimised tract-based spatial statistics protocol for neonates: applications to prematurity and chronic lung disease
    Gareth Ball
    Institute of Clinical Sciences, Imperial College and MRC Clinical Sciences Centre, Hammersmith Hospital, London, UK
    Neuroimage 53:94-102. 2010
    ..These data suggest that potentially modifiable respiratory morbidity is associated with widespread altered white matter microstructure in preterm infants at term-equivalent age...
  38. ncbi Automatic detection and quantification of hippocampal atrophy on MRI in temporal lobe epilepsy: a proof-of-principle study
    Alexander Hammers
    MRC Clinical Sciences Centre and Division of Neuroscience, Faculty of Medicine, Imperial College London, Hammersmith Hospital, DuCane Road, London, UK
    Neuroimage 36:38-47. 2007
    ..The method has the potential to automatically detect unilateral HA, but further work is needed to determine its performance in detecting clinically important bilateral disease...
  39. ncbi Segmentation of brain MRI in young children
    Maria Murgasova
    Visual Information Processing Group, Department of Computing, Imperial College London
    Med Image Comput Comput Assist Interv 9:687-94. 2006
    ..Using this approach we significantly improve the performance of the popular EM segmentation algorithm on brain MRI of young children...
  40. pmc Magnetic resonance imaging of the newborn brain: automatic segmentation of brain images into 50 anatomical regions
    Ioannis S Gousias
    Faculty of Medicine, Imperial College London, and Medical Research Council Clinical Sciences Centre, Hammersmith Hospital, London, United Kingdom
    PLoS ONE 8:e59990. 2013
    ..This registration approach allows the rapid construction of automatically labeled age-specific brain atlases for neonates and the developing brain...
  41. ncbi Automatic anatomical brain MRI segmentation combining label propagation and decision fusion
    Rolf A Heckemann
    Imaging Sciences Department, MRC Clinical Sciences Centre, Imperial College at Hammersmith Hospital Campus, Du Cane Road, London W12 0HS, UK
    Neuroimage 33:115-26. 2006
    ..We demonstrate a practicable procedure that exceeds the accuracy of previous automatic methods and can compete with manual delineations...
  42. ncbi Segmentation of 4D cardiac MR images using a probabilistic atlas and the EM algorithm
    Maria Lorenzo-Valdés
    Visual Information Processing Group, Department of Computing, Imperial College London, 180 Queens Gate, London SW7 2BZ, UK
    Med Image Anal 8:255-65. 2004
    ..93) and myocardium (0.94) when the atlas constructed with volunteers is blurred...
  43. doi Simultaneous multi-scale registration using large deformation diffeomorphic metric mapping
    Laurent Risser
    Institute for Mathematical Science, Imperial College, SW7 2PG, London, UK
    IEEE Trans Med Imaging 30:1746-59. 2011
    ..Results show that our method registers accurately volumetric images containing feature differences at several scales simultaneously with smooth deformations...
  44. ncbi Predicting the shapes of bones at a joint: application to the shoulder
    Yuhui M Yang
    Department of Bioengineering, Imperial College, London, UK
    Comput Methods Biomech Biomed Engin 11:19-30. 2008
    ..A leave one out experiment was performed to test the robustness of this prediction method. The prediction behaviour using this method shows statistically significantly better results than using the mean shape from the training set...
  45. ncbi Automatic segmentation of brain MRIs of 2-year-olds into 83 regions of interest
    Ioannis S Gousias
    Imaging Sciences Department, MRC Clinical Sciences Centre and Department of Pediatrics, Imperial College London, Hammersmith Hospital, Du Cane Road, London W12 0NN, UK
    Neuroimage 40:672-84. 2008
    ..90+/-0.01, 0.90+/-0.01 and 0.88+/-0.03 respectively. This registration approach allows the rapid construction of automatically labelled age-specific brain atlases for children at the age of 2 years...
  46. ncbi Hierarchical statistical shape analysis and prediction of sub-cortical brain structures
    Anil Rao
    Visual Information Processing, Department of Computing, Imperial College London, 180 Queens s Gate, London SW7 2BZ, UK
    Med Image Anal 12:55-68. 2008
    ..We also indicate how the correlation strengths between structures can be used to inform a hierarchical scheme in which partial least squares regression is combined with a model fitting algorithm to further improve prediction accuracy...
  47. ncbi Laplacian Eigenmaps manifold learning for landmark localization in brain MR images
    Ricardo Guerrero
    Biomedical Image Analysis Group, Imperial College London
    Med Image Comput Comput Assist Interv 14:566-73. 2011
    ..We demonstrate this framework in 3D brain MR images from the ADNI database. We show an accuracy of -0.5mm, an increase of at least two fold when compared to traditional approaches such as registration or sliding windows...
  48. ncbi Evaluation of rigid and non-rigid motion compensation of cardiac perfusion MRI
    Hui Xue
    Imaging and Visualization, Siemens Corporate Research, Princeton, NJ, USA
    Med Image Comput Comput Assist Interv 11:35-43. 2008
    ....
  49. ncbi Sample sufficiency and number of modes to retain in statistical shape modelling
    Lin Mei
    Dept of Biosurgery and Surgical Technology Imperial College London, UK
    Med Image Comput Comput Assist Interv 11:425-33. 2008
    ..Our method provides a principled foundation for appropriate selection of the number of modes to retain and determination of sample size sufficiency for statistical shape modelling...
  50. doi Inflammation after trauma: microglial activation and traumatic brain injury
    Anil F Ramlackhansingh
    Centre for Neuroscience, Department of Medicine, Imperial College London, Hammersmith Hospital Campus, London, UK
    Ann Neurol 70:374-83. 2011
    ..In this study, we investigate whether an inflammatory response to TBI persists, and whether this response relates to structural brain abnormalities and cognitive function...
  51. ncbi [11C]Flumazenil PET in temporal lobe epilepsy: do we need an arterial input function or kinetic modeling?
    Alexander Hammers
    MRC Clinical Sciences Centre and Division of Neuroscience, Faculty of Medicine, Imperial College London, Hammersmith Hospital, London, UK
    J Cereb Blood Flow Metab 28:207-16. 2008
    ..Full quantification with an image-independent input should ideally be used in the evaluation of FMZ PET; at least in TLE, intrasubject correlations do not predict equivalent clinical usefulness...
  52. ncbi Longitudinal regional brain volume changes quantified in normal aging and Alzheimer's APP x PS1 mice using MRI
    Satheesh Maheswaran
    Department of Computing, Imperial College, London, UK
    Brain Res 1270:19-32. 2009
    ..The pervasive, age-related structural changes between WT and AD transgenic mice (and mouse and human) suggest subtle but fundamental species differences and AD transgene effects...
  53. doi Image guidance for robotic minimally invasive coronary artery bypass
    Michael Figl
    Department of Computing, Imperial College London, UK
    Comput Med Imaging Graph 34:61-8. 2010
    ..It is hoped that the augmented view can improve the efficiency of TECAB surgery and reduce the conversion rate to more conventional procedures...
  54. pmc Multi-method analysis of MRI images in early diagnostics of Alzheimer's disease
    Robin Wolz
    Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
    PLoS ONE 6:e25446. 2011
    ..The most stable and reliable classification was achieved when combining all available features...
  55. doi Neurological features of epilepsy, ataxia, sensorineural deafness, tubulopathy syndrome
    J Helen Cross
    Neurosciences Unit, Great Ormond Street Hospital for Children NHS Trust and UCL Institute of Child Health, London, UK
    Dev Med Child Neurol 55:846-56. 2013
    ..Here, we provide a detailed characterization of the clinical features of the syndrome to aid patient management with respect to diagnosis, prognostic counselling, and identification of best treatment modalities...
  56. ncbi Automatic construction of 3-D statistical deformation models of the brain using nonrigid registration
    Daniel Rueckert
    Department of Computing, Imperial College, London, UK
    IEEE Trans Med Imaging 22:1014-25. 2003
    ..40 mm at these anatomical landmark positions. We also demonstrate that SDMs can be constructed so as to minimize the bias toward the chosen reference subject...
  57. ncbi Interactive finite element simulation of the beating heart for image-guided robotic cardiac surgery
    Philip Pratt
    Department of Biosurgery and Surgical Technology, Imperial College London, UK
    Stud Health Technol Inform 132:378-83. 2008
    ..The method has been applied initially to volumetric images of a pneumatically-operated beating heart phantom...
  58. ncbi Beyond the g-factor limit in sensitivity encoding using joint histogram entropy
    David J Larkman
    Imaging Sciences Department, Imperial College London, Clinical Sciences Centre, Faculty of Medicine, Hammersmith Hospital Campus, United Kingdom
    Magn Reson Med 55:153-60. 2006
    ..The method preserves image structure, contrast, and lesions even when these were not observable in the reference data. In all cases g-factor was dramatically reduced...
  59. ncbi White matter development in children with benign childhood epilepsy with centro-temporal spikes
    Carolina Ciumas
    1 INSERM U1028, CNRS UMR5292, Centre de Recherche en Neuroscience de Lyon, Translational and Integrative Group in Epilepsy Research TIGER, Universite Lyon 1, Lyon, France
    Brain 137:1095-106. 2014
    ..However, such cross-sectional association does not demonstrate causality, and other hitherto unidentified factors could represent the common cause to part or all of the observed findings...
  60. ncbi Abnormal deep grey matter development following preterm birth detected using deformation-based morphometry
    James P Boardman
    Imaging Sciences Department, MRC Clinical Sciences Centre, Imperial College London, Hammersmith Hospital, Du Cane Road, London W12 0NN, UK
    Neuroimage 32:70-8. 2006
    ..Deformation-based morphometry is a powerful tool for modelling the developing brain in health and disease, and can be used to test putative aetiological factors for injury...