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 object 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 7.5 %, which was higher than the accuracy of conventional region segmentation algorithm, was obtained.
|Number of pages||14|
|Journal||Multimedia Tools and Applications|
|Publication status||Published - 2015 Aug 17|
Bibliographical noteFunding Information:
This research was supported by MSIP (the Ministry of Science, ICT and Future Planning), Korea, under the IT-CRSP (IT Convergence Research Support Program) (NIPA-2013-H0401-13-1001), supervised by the NIPA (National IT Industry Promotion Agency); and by a grant from the Korea Healthcare Technology R&D Project of the Ministry of Health and Wealth of the Republic of Korea (A080369).
© 2014, Springer Science+Business Media New York.
All Science Journal Classification (ASJC) codes
- Media Technology
- Hardware and Architecture
- Computer Networks and Communications