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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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Whangbo, Taeg Keun
College of IT Convergence (컴퓨터공학부(컴퓨터공학전공))
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