Abstract
This paper presents an extended version of the fully automated 3D cerebral vessel reconstruction algorithm developed by Wilson and Noble [11] which is applicable to time-of-flight (TOF) and phase contrast (PC) magnetic resonance angiography (MRA) images. We introduce a Rician distribution for background noise modelling and use a modified EM (Expectation-Maximization) algorithm for the parameter estimation procedure. The proposed algorithm is applied to PC-MRA images. It is shown that the estimated Rician distribution gives a better quality-of-fit to the observed background noise distribution than a Gaussian distribution. In the experiments reported, the segmented 3D vasculature is shown to be qualitatively comparable with the results obtained from higher resolution TOF MRA images.
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© 1999 Springer-Verlag Berlin Heidelberg
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Chung, A.C.S., Noble, J.A. (1999). Statistical 3D Vessel Segmentation Using a Rician Distribution. In: Taylor, C., Colchester, A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI’99. MICCAI 1999. Lecture Notes in Computer Science, vol 1679. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10704282_9
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DOI: https://doi.org/10.1007/10704282_9
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Print ISBN: 978-3-540-66503-8
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