Semi-automatic Liver Segmentation in CT Images Through Intensity Separation and Region Growing

Liver segmentation is considered as a challenge task, and accurate and reliable segmentation of liver is essential of the follow-up of liver treatment. In this paper, a novel liver segmentation method including intensity separation, region growing and morphological hole-filling is presented. Firstly...

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Bibliographic Details
Published in:Procedia computer science 2018, Vol.131, p.220-225
Main Authors: Zhou, Zheng, Xue-chang, Zhang, Si-ming, Zheng, Hua-fei, Xu, Yue-ding, Shi
Format: Article
Language:English
Subjects:
intensity separation
liver segmentation
region growing
surface rendering
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Summary:Liver segmentation is considered as a challenge task, and accurate and reliable segmentation of liver is essential of the follow-up of liver treatment. In this paper, a novel liver segmentation method including intensity separation, region growing and morphological hole-filling is presented. Firstly, intensity separation is employed to increase the difference between the intensities of liver and its adjacent tissues. Then the following region growing algorithm is applied to segment the liver. And the morphological hole-filling is used at last to refine the segmentation results. The proposed method was evaluated with a patient dataset coming from Ningbo Li Hui-li hospital. The validation results and surface rendering show that the method provides a reliable and robust way for liver segmentation. This method could provide a reference for clinical practice.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2018.04.206