Pattern Recognition and Image Analysis

, Volume 24, Issue 1, pp 185–187 | Cite as

Segmentation of liver vessels for surgical purposes

Applied Problems
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Abstract

In this paper we describe a new approach for segmentation of liver from CT images and further the segmentation of liver vessels to create a visualization model for surgical purposes. Since usual approaches, based on density models or edge detection, don’t work well for liver, we investigate the texture of the liver to classify each pixel, whether it lies on the liver-background boundary or outside it. The classifier outputs the boundaries of the liver in each slice, which are used then to create the organ volume. Vessels are segmented then inside the liver volume using a single automatically selected threshold. The result is morphologically closed and smoothed by a Gaussian kernel then.

Keywords

Medical image segmentation texture-based classification thresholding mathematical morphology 

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References

  1. 1.
    M. Sonka and J. M. Fitzpatrick, Handbook of Medical Imaging: Medical Image Processing and Analysis (SPIE Society of Photo-Optical Instrumentation Engi, Bellingham, Washington, 2000), 0819436224.Google Scholar
  2. 2.
    M. Sonka, V. Hlavac, and R. Boyle, Image Processing, Analysis and Machine Vision, 3rd edition (Thomson Learning, Toronto, 2007), ISBN 049508252X.Google Scholar

Copyright information

© Pleiades Publishing, Ltd. 2014

Authors and Affiliations

  1. 1.The Univerzity of West BohemiaPilsenCzech Republic

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