Abstract
For establishing a plan of Living Donor Liver Transplantation (LDLT), it is very important to estimate the volume of each liver segment. Usually Couinaud’s classification is used to segment a liver, which is based on the liver anatomy. However, it is not easy to perform this method in a 3D space directly. In this paper, a fast segment method based on the hepatic vessel tree was proposed. This method was composed of four main steps: vasculature segmentation, 3D thinning, vascular tree pruning and classification, and vascular projection and curve fitting. This method was validated by application to a 3D liver from CT data, and it was shown to approximate closely Couinaud’s classification with high speed.
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References
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© 2008 Springer-Verlag Berlin Heidelberg
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Huang, Sh., Wang, Bl., Cheng, M., Wu, Wl., Huang, Xy., Ju, Y. (2008). A Fast Method to Segment the Liver According to Couinaud’s Classification. In: Gao, X., Müller, H., Loomes, M.J., Comley, R., Luo, S. (eds) Medical Imaging and Informatics. MIMI 2007. Lecture Notes in Computer Science, vol 4987. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79490-5_33
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DOI: https://doi.org/10.1007/978-3-540-79490-5_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-79489-9
Online ISBN: 978-3-540-79490-5
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