Liver Image Segmentation Using Improved Watershed Method


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This paper introduces an improved watershed algorithm for liver image segmentation. Medical images have complicated structure and the soft tissues have deformation sometimes. To exactly conduct the following image registration or surgery navigation, the image segmentation must identify the changes quickly and accurately. Watershed algorithm has fast speed and good edge location for complex structure, but it is sensitive to noise and has the over-segmentation problem. In this paper, pre-processing and post-processing methods are proposed during watershed segmentation procedure. According to the thresholds of region area and gray difference between adjacent regions, the image noise is reduced at pre-processing stage and the over-segmented regions are merged at post-processing part. Through the experiment of two similar liver images, we can see the segmented images have clear outline and the difference of two images can be identified obviously.



Edited by:

Qi Luo






X. H. Xie et al., "Liver Image Segmentation Using Improved Watershed Method", Applied Mechanics and Materials, Vols. 58-60, pp. 1311-1316, 2011

Online since:

June 2011




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