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An Improved Random Walker with Bayes Model for Volumetric Medical Image Segmentation
Joint Authors
Han, Xian-Hua
Chen, Yen-Wei
Zeng, Xiang-Yan
Lin, Lanfen
Hu, Hongjie
Dong, Chunhua
Naghedolfeizi, Masoud
Aberra, Dawit
Source
Journal of Healthcare Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-23
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Random walk (RW) method has been widely used to segment the organ in the volumetric medical image.
However, it leads to a very large-scale graph due to a number of nodes equal to a voxel number and inaccurate segmentation because of the unavailability of appropriate initial seed point setting.
In addition, the classical RW algorithm was designed for a user to mark a few pixels with an arbitrary number of labels, regardless of the intensity and shape information of the organ.
Hence, we propose a prior knowledge-based Bayes random walk framework to segment the volumetric medical image in a slice-by-slice manner.
Our strategy is to employ the previous segmented slice to obtain the shape and intensity knowledge of the target organ for the adjacent slice.
According to the prior knowledge, the object/background seed points can be dynamically updated for the adjacent slice by combining the narrow band threshold (NBT) method and the organ model with a Gaussian process.
Finally, a high-quality image segmentation result can be automatically achieved using Bayes RW algorithm.
Comparing our method with conventional RW and state-of-the-art interactive segmentation methods, our results show an improvement in the accuracy for liver segmentation (p<0.001).
American Psychological Association (APA)
Dong, Chunhua& Zeng, Xiang-Yan& Lin, Lanfen& Hu, Hongjie& Han, Xian-Hua& Naghedolfeizi, Masoud…[et al.]. 2017. An Improved Random Walker with Bayes Model for Volumetric Medical Image Segmentation. Journal of Healthcare Engineering،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1181146
Modern Language Association (MLA)
Dong, Chunhua…[et al.]. An Improved Random Walker with Bayes Model for Volumetric Medical Image Segmentation. Journal of Healthcare Engineering No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1181146
American Medical Association (AMA)
Dong, Chunhua& Zeng, Xiang-Yan& Lin, Lanfen& Hu, Hongjie& Han, Xian-Hua& Naghedolfeizi, Masoud…[et al.]. An Improved Random Walker with Bayes Model for Volumetric Medical Image Segmentation. Journal of Healthcare Engineering. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1181146
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1181146