Publication: Outer Wall Segmentation of Abdominal Aortic Aneurysm by Variable Neighborhood Search Through Intensity and Gradient Spaces
Issued Date
2018-08-01
Resource Type
ISSN
1618727X
08971889
08971889
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2-s2.0-85040658459
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Mahidol University
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SCOPUS
Bibliographic Citation
Journal of Digital Imaging. Vol.31, No.4 (2018), 490-504
Suggested Citation
Thanongchai Siriapisith, Worapan Kusakunniran, Peter Haddawy Outer Wall Segmentation of Abdominal Aortic Aneurysm by Variable Neighborhood Search Through Intensity and Gradient Spaces. Journal of Digital Imaging. Vol.31, No.4 (2018), 490-504. doi:10.1007/s10278-018-0049-z Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/45610
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Title
Outer Wall Segmentation of Abdominal Aortic Aneurysm by Variable Neighborhood Search Through Intensity and Gradient Spaces
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Abstract
© 2018, Society for Imaging Informatics in Medicine. Aortic aneurysm segmentation remains a challenge. Manual segmentation is a time-consuming process which is not practical for routine use. To address this limitation, several automated segmentation techniques for aortic aneurysm have been developed, such as edge detection-based methods, partial differential equation methods, and graph partitioning methods. However, automatic segmentation of aortic aneurysm is difficult due to high pixel similarity to adjacent tissue and a lack of color information in the medical image, preventing previous work from being applicable to difficult cases. This paper uses uses a variable neighborhood search that alternates between intensity-based and gradient-based segmentation techniques. By alternating between intensity and gradient spaces, the search can escape from local optima of each space. The experimental results demonstrate that the proposed method outperforms the other existing segmentation methods in the literature, based on measurements of dice similarity coefficient and jaccard similarity coefficient at the pixel level. In addition, it is shown to perform well for cases that are difficult to segment.