Adaptive Level Set Method for Segmentation of Liver Tumors in Minimally Invasive Surgery Using Ultrasound Images

Ultrasound images have been employed in guiding clinical interventional therapy procedures for liver tumor. However, segmenting liver tumor in the ultrasound images presents a unique challenge because of the low-contrast objects in the noisy image. Snakes, or active contours have had limited success...

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Bibliographic Details
Published in2007 1st International Conference on Bioinformatics and Biomedical Engineering Vol. 1; pp. 1091 - 1094
Main Authors Jing Xu, Chen, K., Xiangdong Yang, Wu, D., Senqiang Zhu
Format Conference Proceeding Journal Article
LanguageEnglish
Published IEEE 2007
Subjects
Active contours
Active noise reduction
Image segmentation
Level set
Liver neoplasms
Medical treatment
Minimally invasive surgery
Robustness
Statistics
Ultrasonic imaging
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ISBN9781424411207
1424411203
ISSN2151-7614
DOI10.1109/ICBBE.2007.282

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Summary:Ultrasound images have been employed in guiding clinical interventional therapy procedures for liver tumor. However, segmenting liver tumor in the ultrasound images presents a unique challenge because of the low-contrast objects in the noisy image. Snakes, or active contours have had limited success in such noisy and complex image. In this paper, an adaptive level set method is proposed, which combines the global statistics and boundary statistics instead of image gradient and edge strength .Compared to traditional level set method, the experiment results show that the proposed level set method was feasible , enabled accurate and robust.
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ISBN:9781424411207
1424411203
ISSN:2151-7614
DOI:10.1109/ICBBE.2007.282