DocumentCode
2360830
Title
Effective R2 Map-Based Liver Segmentation Method in an MR Image
Author
Eun, Sung-Jong ; Kwon, Jeongmin ; Kim, Hyeonjin ; Whangbo, Taeg-Keun
Author_Institution
Dept. of Comput. Sci., Gachon Univ., Seongnam, South Korea
fYear
2012
fDate
23-25 May 2012
Firstpage
1
Lastpage
6
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.
Keywords
biomedical MRI; feature extraction; image segmentation; liver; medical image processing; object recognition; MR Image; R2 information; R2 map-based liver segmentation method; computerized processing; feature points; magnetic resonance theory; object recognition; region segmentation algorithm; Brightness; Equations; Feature extraction; Image segmentation; Liver; Magnetic resonance imaging; Mathematical model;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Science and Applications (ICISA), 2012 International Conference on
Conference_Location
Suwon
Print_ISBN
978-1-4673-1402-2
Type
conf
DOI
10.1109/ICISA.2012.6220957
Filename
6220957
Link To Document