Effective R2 map-based liver segmentation method in an MR image
- Authors
- Eun, S.-J.; Kwon, J.; Kim, H.; Whangbo, T.-K.
- Issue Date
- 2012
- Keywords
- 3D region growing; component; MR image; Liver segmentation; R2 map; Texture analysis
- Citation
- 2012 International Conference on Information Science and Applications, ICISA 2012
- Journal Title
- 2012 International Conference on Information Science and Applications, ICISA 2012
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/17459
- DOI
- 10.1109/ICISA.2012.6220957
- ISSN
- 0000-0000
- Abstract
- Object recognition is usually processed based on region segmentation algorithm. Region segmentation in the IT field is carried out by computerized processing of various input information such as brightness, shape, and pattern analysis. If the information mentioned does not make sense, however, many limitations could occur with region segmentation during computer processing. Therefore, this paper suggests effective region segmentation method based on R2 information within the magnetic resonance (MR) theory. In this study, the experiment had been conducted using images including the liver region and by setting up feature points of R2 map as seed points for region growing to enable region segmentation even when the border line was not clear. As a result, an average area difference of 8.5%, which was higher than the accuracy of conventional region segmentation algorithm, was obtained. © 2012 IEEE.
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Collections - IT융합대학 > 컴퓨터공학과 > 1. Journal Articles
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