Publications
1026 results found
Rueckert D, Aljabar P, 2010, Nonrigid Registration of Medical Images: Theory, Methods, and Applications, IEEE SIGNAL PROCESSING MAGAZINE, Vol: 27, Pages: 113-119, ISSN: 1053-5888
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- Citations: 51
Keihaninejad S, Heckemann RA, Gousias IS, et 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
Heckemann RA, Keihaninejad S, Aljabar P, et 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
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- Citations: 143
Robinson EC, Hammers A, Ericsson A, et al., 2010, Identifying population differences in whole-brain structural networks: A machine learning approach, NEUROIMAGE, Vol: 50, Pages: 910-919, ISSN: 1053-8119
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- Citations: 64
Lotjonen JMP, Wolz R, Koikkalainen JR, et al., 2010, Fast and robust multi-atlas segmentation of brain magnetic resonance images, NEUROIMAGE, Vol: 49, Pages: 2352-2365, ISSN: 1053-8119
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- Citations: 287
Wolz R, Aljabar P, Hajnal JV, et al., 2010, LEAP: Learning embeddings for atlas propagation, NEUROIMAGE, Vol: 49, Pages: 1316-1325, ISSN: 1053-8119
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- Citations: 184
Figl M, Rueckert D, Hawkes D, et al., 2010, Image guidance for robotic minimally invasive coronary artery bypass, COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, Vol: 34, Pages: 61-68, ISSN: 0895-6111
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- Citations: 27
Hu M, Hawkes DJ, Penney GP, et al., 2010, A ROBUST MOSAICING METHOD FOR ROBOTIC ASSISTED MINIMALLY INVASIVE SURGERY, 7th International Conference on Informatics in Control, Automation and Robotics, Publisher: INSTICC-INST SYST TECHNOLOGIES INFORMATION CONTROL & COMMUNICATION, Pages: 206-211
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- Citations: 1
Zhang H, Yushkevich PA, Rueckert D, et al., 2010, A Computational White Matter Atlas for Aging with Surface-Based Representation of Fasciculi, 4th Workshop on Biomedical Image Registration, Publisher: SPRINGER-VERLAG BERLIN, Pages: 83-+, ISSN: 0302-9743
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- Citations: 25
Darvann TA, Hermann NV, Larsen P, et al., 2010, AUTOMATED QUANTIFICATION AND ANALYSIS OF MANDIBULAR ASYMMETRY, 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Publisher: IEEE, Pages: 416-419, ISSN: 1945-7928
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- Citations: 2
Figl M, Rueckert D, Edwards P, 2010, Registration of a Cardiac Motion Model to Video for Augmented Reality Image Guidance of Coronary Artery Bypass, 11th International Congress of the IUPESM/World Congress on Medical Physics and Biomedical Engineering
Risser L, Vialard F-X, Murgasova M, et al., 2010, Large Deformation Diffeomorphic Registration Using Fine and Coarse Strategies, 4th Workshop on Biomedical Image Registration, Publisher: SPRINGER-VERLAG BERLIN, Pages: 186-+, ISSN: 0302-9743
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- Citations: 1
Zhang DP, Risser L, Friman O, et al., 2010, Nonrigid Registration and Template Matching for Coronary Motion Modeling from 4D CTA, 4th Workshop on Biomedical Image Registration, Publisher: SPRINGER-VERLAG BERLIN, Pages: 210-+, ISSN: 0302-9743
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- Citations: 5
Wolz R, Aljabar P, Hajnal JV, et al., 2010, Manifold Learning for Biomarker Discovery in MR Imaging, 1st International Workshop on Machine Learning in Medical Imaging, Publisher: SPRINGER-VERLAG BERLIN, Pages: 116-+, ISSN: 0302-9743
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- Citations: 18
Shi W, Murgasova M, Edwards P, et al., 2010, Simultaneous Reconstruction of 4-D Myocardial Motion from Both Tagged and Untagged MR Images Using Nonrigid Image Registration, 5th International Workshop on Medical Imaging and Augmented Reality, Publisher: SPRINGER-VERLAG BERLIN, Pages: 98-107, ISSN: 0302-9743
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- Citations: 2
Hu M, Penney G, Rueckert D, et al., 2010, A Robust Mosaicing Method with Super-Resolution for Optical Medical Images, 5th International Workshop on Medical Imaging and Augmented Reality, Publisher: SPRINGER-VERLAG BERLIN, Pages: 373-+, ISSN: 0302-9743
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- Citations: 12
Zhang DP, Risser L, Vialard F-X, et al., 2010, Coronary Motion Estimation from CTA Using Probability Atlas and Diffeomorphic Registration, 5th International Workshop on Medical Imaging and Augmented Reality, Publisher: SPRINGER-VERLAG BERLIN, Pages: 78-+, ISSN: 0302-9743
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- Citations: 1
Deligianni F, Robinson EC, Beckmann CF, et al., 2010, INFERENCE OF FUNCTIONAL CONNECTIVITY FROM STRUCTURAL BRAIN CONNECTIVITY, 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Publisher: IEEE, Pages: 1113-1116, ISSN: 1945-7928
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- Citations: 7
Karim R, Juli C, Malcolme-Lawes L, et al., 2010, Automatic Segmentation of Left Atrial Geometry from Contrast-Enhanced Magnetic Resonance Images Using a Probabilistic Atlas, 1st International Workshop on Statistical Atlases and Computational Models of the Heart, Publisher: SPRINGER-VERLAG BERLIN, Pages: 134-+, ISSN: 0302-9743
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- Citations: 10
Murgasova M, Srinivasan L, Gousias IS, et al., 2010, CONSTRUCTION OF A DYNAMIC 4D PROBABILISTIC ATLAS FOR THE DEVELOPING BRAIN, 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Publisher: IEEE, Pages: 952-955, ISSN: 1945-7928
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- Citations: 1
Zhang DP, Risser L, Metz C, et al., 2010, CORONARY ARTERY MOTION MODELING FROM 3D CARDIAC CT SEQUENCES USING TEMPLATE MATCHING AND GRAPH SEARCH, 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Publisher: IEEE, Pages: 1053-1056, ISSN: 1945-7928
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- Citations: 3
Robinson EC, Rueckert D, Hammers A, et al., 2010, PROBABILISTIC WHITE MATTER AND FIBER TRACT ATLAS CONSTRUCTION, 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Publisher: IEEE, Pages: 1153-1156, ISSN: 1945-7928
Wolz R, Heckemann RA, Aljabar P, et 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
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- Citations: 2
Risser L, Vialard F-X, Wolz R, et al., 2010, Simultaneous Fine and Coarse Diffeomorphic Registration: Application to Atrophy Measurement in Alzheimer's Disease, 13th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Publisher: SPRINGER-VERLAG BERLIN, Pages: 610-+, ISSN: 0302-9743
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- Citations: 15
Aljabar P, Wolz R, Srinivasan L, et al., 2010, Combining Morphological Information in a Manifold Learning Framework: Application to Neonatal MRI, 13th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Publisher: SPRINGER-VERLAG BERLIN, Pages: 1-+, ISSN: 0302-9743
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- Citations: 17
Zhang DP, Edwards E, Mei L, et al., 2009, 4D motion modeling of the coronary arteries from CT images for robotic assisted minimally invasive surgery, ISSN: 1605-7422
In this paper, we present a novel approach for coronary artery motion modeling from cardiac Computed Tomography( CT) images. The aim of this work is to develop a 4D motion model of the coronaries for image guidance in robotic-assisted totally endoscopic coronary artery bypass (TECAB) surgery. To utilize the pre-operative cardiac images to guide the minimally invasive surgery, it is essential to have a 4D cardiac motion model to be registered with the stereo endoscopic images acquired intraoperatively using the da Vinci robotic system. In this paper, we are investigating the extraction of the coronary arteries and the modelling of their motion from a dynamic sequence of cardiac CT. We use a multi-scale vesselness filter to enhance vessels in the cardiac CT images. The centerlines of the arteries are extracted using a ridge traversal algorithm. Using this method the coronaries can be extracted in near real-time as only local information is used in vessel tracking. To compute the deformation of the coronaries due to cardiac motion, the motion is extracted from a dynamic sequence of cardiac CT. Each timeframe in this sequence is registered to the end-diastole timeframe of the sequence using a non-rigid registration algorithm based on free-form deformations. Once the images have been registered a dynamic motion model of the coronaries can be obtained by applying the computed free-form deformations to the extracted coronary arteries. To validate the accuracy of the motion model we compare the actual position of the coronaries in each time frame with the predicted position of the coronaries as estimated from the non-rigid registration. We expect that this motion model of coronaries can facilitate the planning of TECAB surgery, and through the registration with real-time endoscopic video images it can reduce the conversion rate from TECAB to conventional procedures. © 2009 Copyright SPIE - The International Society for Optical Engineering.
Yang GZ, Hawkes D, Rueckert D, et al., 2009, Medical Image Computing and Computer-Assisted Intervention - MICCAI2009: Preface, ISBN: 9783642042706
Sjogreen-Gleisner K, Rueckert D, Ljungberg M, 2009, Registration of serial SPECT/CT images for three-dimensional dosimetry in radionuclide therapy, PHYSICS IN MEDICINE AND BIOLOGY, Vol: 54, Pages: 6181-6200, ISSN: 0031-9155
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- Citations: 23
Babalola KO, Patenaude B, Aljabar P, et al., 2009, An evaluation of four automatic methods of segmenting the subcortical structures in the brain., Neuroimage, Vol: 47, Pages: 1435-1447
The automation of segmentation of subcortical structures in the brain is an active research area. We have comprehensively evaluated four novel methods of fully automated segmentation of subcortical structures using volumetric, spatial overlap and distance-based measures. Two methods are atlas-based - classifier fusion and labelling (CFL) and expectation-maximisation segmentation using a brain atlas (EMS), and two incorporate statistical models of shape and appearance - profile active appearance models (PAM) and Bayesian appearance models (BAM). Each method was applied to the segmentation of 18 subcortical structures in 270 subjects from a diverse pool varying in age, disease, sex and image acquisition parameters. Our results showed that all four methods perform on par with recently published methods. CFL performed better than the others according to all three classes of metrics. In summary over all structures, the ranking by the Dice coefficient was CFL, BAM, joint EMS and PAM. The Hausdorff distance ranked the methods as CFL, joint PAM and BAM, EMS, whilst percentage absolute volumetric difference ranked them as joint CFL and PAM, joint BAM and EMS. Furthermore, as we had four methods of performing segmentation, we investigated whether the results obtained by each method were more similar to each other than to the manual segmentations using Williams' Index. Reassuringly, the Williams' Index was close to 1 for most subjects (mean=1.02, sd=0.05), indicating better agreement of each method with the gold standard than with the other methods. However, 2% of cases (mainly amygdala and nucleus accumbens) had values outside 3 standard deviations of the mean.
Gousias IS, Hammers A, Counsell SJ, et al., 2009, A NEW RESOURCE FOR IMAGING RESEARCH IN NEONATES: MANUALLY DEFINED BRAIN ATLASES
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