Imperial College London

ProfessorDanielRueckert

Faculty of EngineeringDepartment of Computing

Head of Department of Computing
 
 
 
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Contact

 

+44 (0)20 7594 8333d.rueckert Website

 
 
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Location

 

568Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

723 results found

Ball G, Boardman JP, Aljabar P, Pandit A, Arichi T, Merchant N, Rueckert D, Edwards AD, Counsell SJet al., 2013, The influence of preterm birth on the developing thalamocortical connectome, CORTEX, Vol: 49, Pages: 1711-1721, ISSN: 0010-9452

Journal article

Shi W, Jantsch M, Aljabar P, Pizarro L, Bai W, Wang H, O'Regan D, Zhuang X, Rueckert Det al., 2013, Temporal sparse free-form deformations, Medical Image Analysis

Journal article

Wu X, Housden J, Ma Y, Rueckert D, Rhode KSet al., 2013, Real-time catheter extraction from 2D X-ray fluoroscopic and 3D echocardiographic images for cardiac interventions, Pages: 198-206, ISSN: 0302-9743

X-ray fluoroscopic images are widely used for image guidance in cardiac electrophysiology (EP) procedures to diagnose or treat cardiac arrhythmias based on catheter ablation. However, the main disadvantage of fluoroscopic imaging is the lack of soft tissue information and harmful radiation. In contrast, ultrasound (US) has the advantages of low-cost, non-radiation, and high contrast in soft tissue. In this paper we propose a framework to extract the catheter from both X-ray and US images in real time for cardiac interventions. The catheter extraction from X-ray images is based on SURF features, local patch analysis and Kalman filtering to acquire a set of sorted key points representing the catheter. At the same time, the transformation between the X-ray and US images can be obtained via 2D/3D rigid registration between a 3D model of the US probe and its projection on X-ray images. By backprojecting the information about the catheter location in the X-ray images to the US images the search space can be drastically reduced. The extraction of the catheter from US is based on 3D SURF feature clusters, graph model building, A*algorithm and B-spline smoothing. Experiments show the overall process can be achieved in 2.72 seconds for one frame and the reprojected error is 1.99 mm on average. © 2013 Springer-Verlag.

Conference paper

Antila K, Lotjonen J, Thurfjell L, Laine J, Massimini M, Rueckert D, Zubarev RA, Oresic M, van Gils M, Mattila J, Simonsen AH, Waldemar G, Soininen Het al., 2013, The PredictAD project: development of novel biomarkers and analysis software for early diagnosis of the Alzheimer's disease, INTERFACE FOCUS, Vol: 3, ISSN: 2042-8898

Journal article

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

Wang Z, Wolz R, Tong T, Rueckert Det al., 2013, Spatially Aware Patch-based Segmentation (SAPS): An alternative patch-based segmentation framework, Pages: 93-103, ISSN: 0302-9743

Patch-based segmentation has been shown to be successful in a range of label propagation applications. Performing patch-based segmentation can be seen as a k-nearest neighbour problem as the labelling of each voxel is determined according to the distances to its most similar patches. However, the reliance on a good affine registration given the use of limited search windows is a potential weakness. This paper presents a novel alternative framework which combines the use of kNN search structures such as ball trees and a spatially weighted label fusion scheme to search patches in large regional areas to overcome the problem of limited search windows. Our proposed framework (SAPS) provides an improvement in the Dice metric of the results compared to that of existing patch-based segmentation frameworks. © 2013 Springer-Verlag.

Conference paper

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

Xi J, Lamata P, Niederer S, Land S, Shi W, Zhuang X, Ourselin S, Duckett SG, Shetty AK, Rinaldi CA, Rueckert D, Razavi R, Smith NPet al., 2013, The estimation of patient-specific cardiac diastolic functions from clinical measurements, MEDICAL IMAGE ANALYSIS, Vol: 17, Pages: 133-146, ISSN: 1361-8415

Journal article

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

Wang H, Shi W, Zhuang X, Wu X, Tung K-P, Ourselin S, Edwards P, Rueckert Det al., 2013, Landmark Detection and Coupled Patch Registration for Cardiac Motion Tracking, Conference on Medical Imaging - Image Processing, Publisher: SPIE-INT SOC OPTICAL ENGINEERING, ISSN: 0277-786X

Conference paper

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

Guerrero R, Rueckert D, 2013, Data-specific Feature Point Descriptor Matching Using Dictionary Learning and Graphical Models, Conference on Medical Imaging - Image Processing, Publisher: SPIE-INT SOC OPTICAL ENGINEERING, ISSN: 0277-786X

Conference paper

Weiss N, Rueckert D, Rao A, 2013, Multiple Sclerosis Lesion Segmentation Using Dictionary Learning and Sparse Coding, 16th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Publisher: SPRINGER-VERLAG BERLIN, Pages: 735-742, ISSN: 0302-9743

Conference paper

Tung K-P, Bei W-J, Shi W-Z, Wang H-Y, Tong T, De Silva R, Edwards E, Rueckert Det al., 2013, MULTI-ATLAS BASED NEOINTIMA SEGMENTATION IN INTRAVASCULAR CORONARY OCT, IEEE 10th International Symposium on Biomedical Imaging - From Nano to Macro (ISBI), Publisher: IEEE, Pages: 1280-1283, ISSN: 1945-7928

Conference paper

Wu X, Housden J, Varma N, Ma Y, Rueckert D, Rhode Ket al., 2013, CATHETER TRACKING IN 3D ECHOCARDIOGRAPHIC SEQUENCES BASED ON TRACKING IN 2D X-RAY SEQUENCES FOR CARDIAC CATHETERIZATION INTERVENTIONS, IEEE 10th International Symposium on Biomedical Imaging - From Nano to Macro (ISBI), Publisher: IEEE, Pages: 25-28, ISSN: 1945-7928

Conference paper

Jantsch M, Rueckert D, Price AN, Hajnal JVet al., 2013, 3D CARDIAC CINE RECONSTRUCTION FROM FREE-BREATHING 2D REAL-TIME IMAGE ACQUISITIONS USING ITERATIVE MOTION CORRECTION, IEEE 10th International Symposium on Biomedical Imaging - From Nano to Macro (ISBI), Publisher: IEEE, Pages: 812-815, ISSN: 1945-7928

Conference paper

Bentley P, Ganesalingam J, Dias A, Mehta A, Sharma P, Halse O, Rueckert Det al., 2013, Hyperacute fingerprinting: CT brain machine-learning predicts response to thrombolysis

Poster

Liu L, Shi W, Rueckert D, Hu M, Ourselin S, Zhuang Xet al., 2013, Model-Guided Directional Minimal Path for Fully Automatic Extraction of Coronary Centerlines from Cardiac CTA, 16th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Publisher: SPRINGER-VERLAG BERLIN, Pages: 542-549, ISSN: 0302-9743

Conference paper

Shi W, Caballero J, Ledig C, Zhuang X, Bai W, Bhatia K, de Marvao AMSM, Dawes T, O'Regan D, Rueckert Det al., 2013, Cardiac Image Super-Resolution with Global Correspondence Using Multi-Atlas PatchMatch, 16th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Publisher: SPRINGER-VERLAG BERLIN, Pages: 9-16, ISSN: 0302-9743

Conference paper

Schirmer M, Ball G, Counsell SJ, Edwards AD, Rueckert D, Hajnal JV, Aljabar Pet al., 2013, Normalisation of Neonatal Brain Network Measures Using Stochastic Approaches, 16th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Publisher: SPRINGER-VERLAG BERLIN, Pages: 574-581, ISSN: 0302-9743

Conference paper

Keraudren K, Kyriakopoulou V, Rutherford M, Hajnal JV, Rueckert Det al., 2013, Localisation of the Brain in Fetal MRI Using Bundled SIFT Features, 16th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Publisher: SPRINGER-VERLAG BERLIN, Pages: 582-589, ISSN: 0302-9743

Conference paper

Wang Z, Donoghue C, Rueckert D, 2013, Patch-Based Segmentation without Registration: Application to Knee MRI, 4th International Workshop on Machine Learning in Medical Imaging (MLMI) in Conjunction with the 16th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Publisher: SPRINGER-VERLAG BERLIN, Pages: 98-105, ISSN: 0302-9743

Conference paper

Tong T, Wolz R, Gao Q, Hajnal JV, Rueckert Det al., 2013, Multiple Instance Learning for Classification of Dementia in Brain MRI, 16th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Publisher: SPRINGER-VERLAG BERLIN, Pages: 599-606, ISSN: 0302-9743

Conference paper

Chu C, Oda M, Kitasaka T, Misawa K, Fujiwara M, Hayashi Y, Nimura Y, Rueckert D, Mori Ket al., 2013, Multi-organ Segmentation Based on Spatially-Divided Probabilistic Atlas from 3D Abdominal CT Images, 16th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Publisher: SPRINGER-VERLAG BERLIN, Pages: 165-172, ISSN: 0302-9743

Conference paper

Chabiniok R, Wong J, Giese D, Nordsletten D, Shi W, Greil G, Rueckert D, Razavi R, Schaeffter T, Smith Net al., 2013, Flow Analysis in Cardiac Chambers Combining Phase Contrast, 3D Tagged and Cine MRI, 7th International Conference on Functional Imaging and Modeling of the Heart (FIMH), Publisher: SPRINGER-VERLAG BERLIN, Pages: 360-369, ISSN: 0302-9743

Conference paper

Zhuang X, Shi W, Wang H, Rueckert D, Ourselin Set al., 2013, Computation on shape manifold for atlas generation: application to whole heart segmentation of cardiac MRI, Conference on Medical Imaging - Image Processing, Publisher: SPIE-INT SOC OPTICAL ENGINEERING, ISSN: 0277-786X

Conference paper

Chu C, Oda M, Kitasaka T, Misawa K, Fujiwara M, Hayashi Y, Wolz R, Rueckert D, Mori Ket al., 2013, Multi-organ Segmentation from 3D Abdominal CT Images using Patient-Specific Weighted-probabilistic Atlas, Conference on Medical Imaging - Image Processing, Publisher: SPIE-INT SOC OPTICAL ENGINEERING, ISSN: 0277-786X

Conference paper

Baumgartner CF, Kolbitsch C, McClelland JR, Rueckert D, King APet al., 2013, Groupwise simultaneous manifold alignment for high-resolution dynamic MR imaging of respiratory motion., Pages: 232-243, ISSN: 1011-2499

Respiratory motion is a complicating factor for many applications in medical imaging and there is significant interest in dynamic imaging that can be used to estimate such motion. Magnetic resonance imaging (MRI) is an attractive modality for motion estimation but current techniques cannot achieve good image contrast inside the lungs. Manifold learning is a powerful tool to discover the underlying structure of high-dimensional data. Aligning the manifolds of multiple datasets can be useful to establish relationships between different types of data. However, the current state-of-the-art in manifold alignment is not robust to the wide variations in manifold structure that may occur in clinical datasets. In this work we propose a novel, fully automatic technique for the simultaneous alignment of large numbers of manifolds with varying manifold structure. We apply the technique to reconstruct high-resolution and high-contrast dynamic 3D MRI images from multiple 2D datasets for the purpose of respiratory motion estimation. The proposed method is validated on synthetic data with known ground truth and real data. We demonstrate that our approach can be applied to reconstruct significantly more accurate and consistent dynamic images of the lungs compared to the current state-of-the-art in manifold alignment.

Conference paper

Gao Q, Chang PL, Rueckert D, Ali SM, Cohen D, Pratt P, Mayer E, Yang GZ, Darzi A, Edwards PJet al., 2013, Modeling of the bony pelvis from MRI using a multi-atlas AE-SDM for registrationand tracking in image-guided robotic prostatectomy, Computerized Medical Imaging and Graphics

Journal article

Munoz-Ruiz MA, Hartikainen P, Koikkalainen J, Wolz R, Julkunen V, Niskanen E, Herukka S-K, Kivipelto M, Vanninen R, Rueckert D, Liu Y, Lotjonen J, Soininen Het al., 2012, Structural MRI in Frontotemporal Dementia: Comparisons between Hippocampal Volumetry, Tensor-Based Morphometry and Voxel-Based Morphometry, PLOS ONE, Vol: 7, ISSN: 1932-6203

Journal article

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