Image-to-Physical Registration for Image-Guided Interventions Using 3-D Ultrasound and an Ultrasound Imaging Model

Authors:
Andrew P. King;Ying-Liang Ma;Cheng Yao;Christian Jansen;Reza Razavi;Kawal S. Rhode;Graeme P. Penney
Affiliations:
Division of Imaging Sciences, King's College London, U.K.;Division of Imaging Sciences, King's College London, U.K.;Division of Imaging Sciences, King's College London, U.K.;Division of Imaging Sciences, King's College London, U.K.;Division of Imaging Sciences, King's College London, U.K.;Division of Imaging Sciences, King's College London, U.K.;Division of Imaging Sciences, King's College London, U.K.
Venue:
IPMI '09 Proceedings of the 21st International Conference on Information Processing in Medical Imaging
Year:
2009

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Abstract

We present a technique for automatic intensity-based image-to-physical registration of a 3-D segmentation for image-guided interventions. The registration aligns the segmentation with tracked and calibrated 3-D ultrasound (US) images of the target region. The technique uses a probabilistic framework and explicitly incorporates a model of the US image acquisition process. The rigid body registration parameters are varied to maximise the likelihood that the real US image(s) were formed using the US imaging model from the probe transducer position. The proposed technique is validated on images segmented from cardiac magnetic resonance imaging (MRI) data and 3-D US images acquired from 3 volunteers and 1 patient. We show that the accuracy of the algorithm is 2.6-4.2mm and the capture range is 9-18mm. The proposed technique has the potential to provide accurate image-to-physical registrations for a range of image guidance applications.