Effective object segmentation based on physical theory in an MR image

Sung Jong Eun; Hyeonjin Kim; Jung Wook Park; Taeg Keun Whangbo

doi:10.1007/s11042-014-2089-9

Effective object segmentation based on physical theory in an MR image

Sung Jong Eun, Hyeonjin Kim, Jung Wook Park, Taeg Keun Whangbo

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

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 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.

Original language	English
Pages (from-to)	6273-6286
Number of pages	14
Journal	Multimedia Tools and Applications
Volume	74
Issue number	16
DOIs	https://doi.org/10.1007/s11042-014-2089-9
Publication status	Published - 2015 Aug 17

Bibliographical note

Funding 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).

Publisher Copyright:
© 2014, Springer Science+Business Media New York.

All Science Journal Classification (ASJC) codes

Software
Media Technology
Hardware and Architecture
Computer Networks and Communications

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10.1007/s11042-014-2089-9

Cite this

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title = "Effective object segmentation based on physical theory in an MR image",

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 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.",

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AU - Eun, Sung Jong

AU - Kim, Hyeonjin

AU - Park, Jung Wook

AU - Whangbo, Taeg Keun

N1 - Funding 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). Publisher Copyright: © 2014, Springer Science+Business Media New York.

PY - 2015/8/17

Y1 - 2015/8/17

N2 - 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.

AB - 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.

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Effective object segmentation based on physical theory in an MR image

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