Dr. Andrew P. King Profile

Dr. Andrew P. King

at King's College London

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Author

Publications (9)

Proceedings Article | 20 March 2015 Paper

Remapping of digital subtraction angiography on a standard fluoroscopy system using 2D-3D registration

Mazen Alhrishy, Andreas Varnavas, Alexis Guyot, Tom Carrell, Andrew King, Graeme Penney

Proceedings Volume 9413, 94131O (2015) https://doi.org/10.1117/12.2082023

KEYWORDS: Image registration, Angiography, Visualization, Image segmentation, Image enhancement, Computed tomography, X-rays, Kidney, Blood vessels, Solids

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Proceedings Article | 14 March 2009 Paper

Spatial compounding of large sets of 3D echocardiography images

Cheng Yao, John Simpson, Christian H. P. Jansen, Andrew King, Graeme Penney

Proceedings Volume 7265, 726515 (2009) https://doi.org/10.1117/12.810906

KEYWORDS: Signal to noise ratio, Image registration, 3D image processing, Image quality, Ultrasonography, Echocardiography, Tissues, Image processing, Optical inspection, Blood

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Proceedings Article | 13 March 2009 Paper

Echocardiography to magnetic resonance image registration for use in image-guide electrophysiology procedures

YingLiang Ma, Kawal Rhode, Andrew King, Dennis Cauldfield, Michael Cooklin, Reza Razavi, Graeme Penney

Proceedings Volume 7261, 72610Q (2009) https://doi.org/10.1117/12.810999

KEYWORDS: Magnetic resonance imaging, Image registration, 3D image processing, X-rays, Ultrasonography, Image segmentation, X-ray imaging, Echocardiography, Electrophysiology, 3D modeling

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Proceedings Article | 25 March 2008 Paper

Validation of the use of photogrammetry to register pre-procedure MR images to intra-procedure patient position for image-guided cardiac catheterization procedures

Gang Gao, Segolene Tarte, Andy King, Yingliang Ma, Phani Chinchapatnam, Tobias Schaeffter, Reza Razavi, Dave Hawkes, Derek Hill, Kawal Rhode

Proceedings Volume 6918, 69181Q (2008) https://doi.org/10.1117/12.770113

KEYWORDS: Magnetic resonance imaging, Chest, Photogrammetry, Imaging systems, Cardiac catheterization, Electrophysiology, 3D image processing, 3D modeling, Image registration, X-rays

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Proceedings Article | 25 March 2008 Paper

Evaluation of the use of multimodality skin markers for the registration of pre-procedure cardiac MR images and intra-procedure x-ray fluoroscopy images for image guided cardiac electrophysiology procedures

Kawal Rhode, Yingliang Ma, Angela Chandrasena, Andrew King, Gang Gao, Phani Chinchapatnam, Maxime Sermesant, David Hawkes, Tobias Schaeffter, Jaswinder Gill, Reza Razavi

Proceedings Volume 6918, 69181R (2008) https://doi.org/10.1117/12.770172

KEYWORDS: Skin, Image registration, Magnetic resonance imaging, X-rays, X-ray imaging, Fluoroscopy, Photovoltaics, Data modeling, Angiography, Electrophysiology

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Proceedings Article | 25 March 2008 Paper

Ultrasound calibration using intensity-based image registration: for application in cardiac catheterization procedures

Y. Ma, K. Rhode, G. Gao, A. King, P. Chinchapatnam, T. Schaeffter, D. Hawkes, R. Razavi, G. Penney

Proceedings Volume 6918, 69180O (2008) https://doi.org/10.1117/12.770174

KEYWORDS: Calibration, Image registration, Ultrasonography, Liver, Transducers, 3D image processing, Optical tracking, Transform theory, Image filtering, Heart

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Proceedings Article | 20 March 2008 Paper

A technique for respiratory motion correction in image guided cardiac catheterisation procedures

A. King, R. Boubertakh, K. L. Ng, Y. L. Ma, P. Chinchapatnam, G. Gao, T. Schaeffter, D. Hawkes, R. Razavi, K. Rhode

Proceedings Volume 6918, 691816 (2008) https://doi.org/10.1117/12.769377

KEYWORDS: Motion models, X-rays, X-ray imaging, Magnetic resonance imaging, Data modeling, Affine motion model, Image registration, 3D modeling, Heart, Cardiac catheterization

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Proceedings Article | 11 March 2008 Paper

A novel framework for multi-modal intensity-based similarity measures based on internal similarity

Graeme Penney, Lewis Griffin, Andrew King, David Hawkes

Proceedings Volume 6914, 69140X (2008) https://doi.org/10.1117/12.769402

KEYWORDS: Image registration, Image enhancement, 3D image enhancement, Image processing, Ultrasonography, Magnetic resonance imaging, 3D image processing, Computed tomography, Bone, Gold

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We present a novel framework for describing intensity-based multi-modal similarity measures. Our framework is based around a concept of internal, or self, similarity. Firstly the locations of multiple regions or patches which are "similar" to each other are identified within a single image. The term "similar" is used here to represent a generic intra-modal similarity measure. Then if we examine a second image in the same locations, and this image is registered to the first image, we should find that the patches in these locations are also "similar", though the actual features in the patches when compared between the images could be very different. We propose that a measure based on this principle could be used as an inter-modal similarity measure because, as the two images become increasingly misregistered then the patches within the second image should become increasingly dissimilar. Therefore, our framework results in an inter-modal similarity measure by using two intra-modal similarity measures applied separately within each image. In this paper we describe how popular multi-modal similarity measures such as mutual information can be described within this framework. In addition the framework has the potential to allow the formation of novel similarity measures which can register using regional information, rather than individual pixel/voxel intensities. An example similarity measure is produced and its ability to guide a registration algorithm is investigated. Registration experiments are carried out using three datasets. The pairs of images to be registered were specifically chosen as they were expected to challenge (i.e. result in misregistrations) standard intensity-based measures, such as mutual information. The images include synthetic data, cadaver data and clinical data and cover a range of modalities. Our experiments show that our proposed measure is able to achieve accurate registrations where standard intensity-based measures, such as mutual information, fail.

Proceedings Article | 5 May 2004 Paper

Tracking alignment of sparse ultrasound with preoperative images of the liver and an interventional plan using models of respiratory motion and deformation

Jane Blackall, Graeme Penney, Andrew King, Andreas Adam, David Hawkes

Proceedings Volume 5367, (2004) https://doi.org/10.1117/12.535180

KEYWORDS: Image registration, Liver, Ultrasonography, Motion models, Magnetic resonance imaging, Data modeling, 3D image processing, Modeling, 3D modeling, Visualization

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Showing 5 of 9 publications

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