Interactive segmentation of medical images using belief propagation with level sets

In this paper, we propose an interactive segmentation method to apply user information during the segmentation of a specific anatomic structure. This method is formulated to use belief propagation to minimize a global cost function according to local level sets. The propagation starts with one user...

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Bibliographic Details
Main Authors: Yingxuan Zhu, Cheng, S, Goel, A
Format: Conference Proceeding
Language:English
Subjects:
Belief propagation
Biomedical imaging
Image segmentation
Interactive segmentation
Level set
level set method
Liver
medical imaging
Pixel
Shape
user information
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Description
Summary:In this paper, we propose an interactive segmentation method to apply user information during the segmentation of a specific anatomic structure. This method is formulated to use belief propagation to minimize a global cost function according to local level sets. The propagation starts with one user labeled point, and iteratively extends the user information from the labeled pixel to its neighborhood by calculating the beliefs of the pixels in the same level as the labeled pixel. Since the segmentation relies on both local user information and global image features, it is less interrupted by noise, and works well even the target is not obvious to its neighbor. The promising segmentation results also show that our method is robust to the objects with high shape variation and inhomogeneous intensity value appearance.
ISSN:1522-4880
2381-8549
DOI:10.1109/ICIP.2010.5651171