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Thesis

Three-dimensional geometric image analysis for interventional electrophysiology

Abstract:

Improving imaging hardware, computational power, and algorithmic design are driving advances in interventional medical imaging. We lay the groundwork here for more effective use of machine learning and image registration in clinical electrophysiology.

To achieve identification of atrial fibrosis using image data, we registered the electroanatomic map (EAM) data of atrial fibrillation (AF) patients undergoing pulmonary vein isolation (PVI) with MR (n = 16) or CT (n ...

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Institution:
University of Oxford
Research group:
Image Analysis Laboratory, Institute of Biomedical Engineering
Oxford college:
Wolfson College
Department:
Medical Sciences Division - Clinical Medicine,Nuffield Department of

Contributors

Role:
Supervisor
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Funding agency for:
John E McManigle
Publication date:
2014
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
Oxford University, UK
URN:
uuid:2f36fa8e-9c64-4807-97c0-25e63398da7e
Local pid:
ora:11439

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