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Group-wise feature-based registration of CT and ultrasound images of spine.

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Title: Group-wise feature-based registration of CT and ultrasound images of spine.
Author: Rasoulian, Abtin; Mousavi, Parvin; Moghari, Mehdi Hedjazi; Foroughi, Pezhman; Abolmaesumi, Purang
Issue Date: 2010
Publicly Available in cIRcle 2011-08-16
Publisher Society of Photo-Optical Instrumentation Engineers
Citation: Rasoulian, Abtin; Mousavi, Parvin; Moghari, Mehdi Hedjazi; Foroughi, Pezhman; Abolmaesumi, Purang. Group-wise feature-based registration of CT and ultrasound images of spine. Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling, edited by Kenneth H. Wong, Michael I. Miga, Proceedings of SPIE, Volume 7625, 76250R, 2010. http://dx.doi.org/10.1117/12.844598
Abstract: Registration of pre-operative CT and freehand intra-operative ultrasound of lumbar spine could aid surgeons in the spinal needle injection which is a common procedure for pain management. Patients are always in a supine position during the CT scan, and in the prone or sitting position during the intervention. This leads to a difference in the spinal curvature between the two imaging modalities, which means a single rigid registration cannot be used for all of the lumbar vertebrae. In this work, a method for group-wise registration of pre-operative CT and intra-operative freehand 2-D ultrasound images of the lumbar spine is presented. The approach utilizes a pointbased registration technique based on the unscented Kalman filter, taking as input segmented vertebrae surfaces in both CT and ultrasound data. Ultrasound images are automatically segmented using a dynamic programming approach, while the CT images are semi-automatically segmented using thresholding. Since the curvature of the spine is different between the pre-operative and the intra-operative data, the registration approach is designed to simultaneously align individual groups of points segmented from each vertebra in the two imaging modalities. A biomechanical model is used to constrain the vertebrae transformation parameters during the registration and to ensure convergence. The mean target registration error achieved for individual vertebrae on five spine phantoms generated from CT data of patients, is 2.47 mm with standard deviation of 1.14 mm. Copyright 2010 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Affiliation: Electrical and Computer Engineering, Dept of
URI: http://hdl.handle.net/2429/36695
Peer Review Status: Reviewed
Scholarly Level: Faculty

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