TA Hybrid Approach using Set Theory (HAST) for Magnetic Resonance (MR) Image Segmentation

Liu Jiang, Chee Kin Ban, Tan Boon Pin, Shuter Borys, Wang Shih-Chang

Abstract

This paper describes a new Hybrid Approach using Set Theory (HAST) for Magnetic Resonance (MR) Image segmentation based on two existing techniques, region-based and level set methods. In our approach, instead of using the typical pipeline methodology to integrate the two techniques, a hybrid set-based methodology will be proposed. To evaluate the effectiveness of HAST, MR images taken from a national hospital that reflects the quality of real world medical images are used. A comparison between the two individual techniques and HAST will also be made to demonstrate the effectiveness of the latter.

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Paper Citation


in Harvard Style

Jiang L., Kin Ban C., Boon Pin T., Borys S. and Shih-Chang W. (2006). TA Hybrid Approach using Set Theory (HAST) for Magnetic Resonance (MR) Image Segmentation . In 6th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2006) ISBN 978-972-8865-55-9, pages 159-168. DOI: 10.5220/0002473801590168


in Bibtex Style

@conference{pris06,
author={Liu Jiang and Chee Kin Ban and Tan Boon Pin and Shuter Borys and Wang Shih-Chang},
title={TA Hybrid Approach using Set Theory (HAST) for Magnetic Resonance (MR) Image Segmentation},
booktitle={6th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2006)},
year={2006},
pages={159-168},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002473801590168},
isbn={978-972-8865-55-9},
}


in EndNote Style

TY - CONF
JO - 6th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2006)
TI - TA Hybrid Approach using Set Theory (HAST) for Magnetic Resonance (MR) Image Segmentation
SN - 978-972-8865-55-9
AU - Jiang L.
AU - Kin Ban C.
AU - Boon Pin T.
AU - Borys S.
AU - Shih-Chang W.
PY - 2006
SP - 159
EP - 168
DO - 10.5220/0002473801590168