Combining multiple true 3D ultrasound image volumes through re-registration and rasterization

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Abstract

We present an accurate and efficient technique to combine and rasterize multiple 3D ultrasound (3DUS) image volumes originally presented in spherical coordinates into a single, 3D Cartesian image that uniformly samples the total field of view. To ensure the consistency of merged image content in overlapping regions, image re-registration was performed by maximizing mutual information (MI). The technique was applied to 22 3DUS image volumes obtained during five neurosurgical patient cases. The computational cost of the approach increases linearly with the number of images involved (average time to combine and rasterize one pair of 3DUS images was 1.5 sec). Interpolation was approximately 20% more accurate in overlapping regions when re-registration was performed before rasterization and minimized feature loss and/or blurring that was evident without re-registration. In addition, we report the average translational (35.2 mm) and rotational (38.5 o ) capture ranges for the MI re-registration of two volumetric 3DUS images. The technique is applicable in any clinical application in which volumetric true 3DUS is acquired. © 2009 Springer-Verlag.

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APA

Ji, S., Roberts, D. W., Hartov, A., & Paulsen, K. D. (2009). Combining multiple true 3D ultrasound image volumes through re-registration and rasterization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5761 LNCS, pp. 795–802). https://doi.org/10.1007/978-3-642-04268-3_98

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