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Authors: Chia-Yen Lee 1 ; Chiun-Sheng Huang 2 ; Yeun-Chung Chang 2 ; Yi-Hong Chou 3 and Chung-Ming Chen 1

Affiliations: 1 National Taiwan University, Taiwan ; 2 National Taiwan University Hospital, Taiwan ; 3 Taipei Veterans General Hospital, Taiwan

Keyword(s): Breast Sonogram, Intensity Inhomogeneity Correction, Segmentation, Fuzzy Cell Competition, Clustering.

Abstract: Intensity inhomogeneity caused by an ultrasonic attenuation beam within the body results in an artifact effect. It frequently degrades the boundary and texture information of a lesion in a breast sonogram. A new Gibbs-weighted K-means segmentation approach with intensity inhomogeneity correction is proposed to cluster the prominent components provided by fuzzy cell competition algorithm for segmenting lesion boundaries automatically with reducing the influence of the intensity inhomogeneity. The information of fuzzy C-means, normalized cut, and cell-based fuzzy cell competition algorithm are combined as the feature vector for cell-based clustering. 49 breast sonograms with intensity inhomogeneity, each from a different subject, are randomly selected for performance analysis. The mean distance between the lesion boundaries attained by the proposed algorithm and the corresponding manually delineated boundaries defined by two radiologists is 1.571±0.513 pixels. (Assessing Chan and Vese level set method for intensity inhomogeneity-correction segmentation in the same way, the mean distance error is3.299±1.203 pixels, for the 49 images.) The results show that Gibbs-weighted K-means segmentation approach with intensity inhomogeneity correction could not only correct the intensity inhomogeneity effect but also improve the segmentation results. (More)

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Paper citation in several formats:
Lee, C.; Huang, C.; Chang, Y.; Chou, Y. and Chen, C. (2012). GIBBS-WEIGHTED K-MEANS SEGMENTATION APPROACH WITH INTENSITY INHOMOGENEITY CORRECTION. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2012) - Volume 2: VISAPP; ISBN 978-989-8565-03-7; ISSN 2184-4321, SciTePress, pages 381-384. DOI: 10.5220/0003946803810384

@conference{visapp12,
author={Chia{-}Yen Lee. and Chiun{-}Sheng Huang. and Yeun{-}Chung Chang. and Yi{-}Hong Chou. and Chung{-}Ming Chen.},
title={GIBBS-WEIGHTED K-MEANS SEGMENTATION APPROACH WITH INTENSITY INHOMOGENEITY CORRECTION},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2012) - Volume 2: VISAPP},
year={2012},
pages={381-384},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003946803810384},
isbn={978-989-8565-03-7},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2012) - Volume 2: VISAPP
TI - GIBBS-WEIGHTED K-MEANS SEGMENTATION APPROACH WITH INTENSITY INHOMOGENEITY CORRECTION
SN - 978-989-8565-03-7
IS - 2184-4321
AU - Lee, C.
AU - Huang, C.
AU - Chang, Y.
AU - Chou, Y.
AU - Chen, C.
PY - 2012
SP - 381
EP - 384
DO - 10.5220/0003946803810384
PB - SciTePress

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