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Proceedings Paper

Segmentation of sonographic breast lesions: fuzzy cell-competition algorithm and bias field reduction
Author(s): Chia-Yen Lee; Chi-Chun Hsieh; Chung-Ming Chen
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Paper Abstract

Bias field is a common phenomenon in a breast sonogram. Although artifacts caused by bias filed may carry important information, e.g., shadowing behind a lesion, they are generally disturbing in the process of automatic boundary delineation for sonographic breast lesions. This paper presents a new segmentation algorithm aiming to decompose the region of interest (ROI) into prominent components while estimating the bias field in the ROI. A prominent component is a contiguous region with a visually perceivable boundary, which might be a noise, an artifact, a substructure of a tissue or a part of breast lesion. The prominent components may be used as the basic constructs for a higher level segmentation algorithm to identify the lesion boundary. The bias field in an ROI is modeled as a spatially-variant Gaussian distribution with a constant variance and spatially-variant means, which is a polynomial surface of order n. The true gray levels of the pixels in a prominent component are assumed to be Gaussian-distributed. The proposed algorithm is formulated as an EM-algorithm composed of two major steps. In the E-step, the ROI is decomposed into prominent components using a new fuzzy cell-competition algorithm based on the bias field and model parameters estimated in the previous M-step. In the M-step, the bias field and model parameters are estimated based on the prominent components derived in the E-step using a least squared approach. The results show that the effect of bias field on segmentation has been reduced and better segmentation results have been attained.

Paper Details

Date Published: 11 March 2008
PDF: 9 pages
Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 691445 (11 March 2008); doi: 10.1117/12.770884
Show Author Affiliations
Chia-Yen Lee, National Taiwan Univ. (Taiwan)
Chi-Chun Hsieh, National Taiwan Univ. (Taiwan)
Chung-Ming Chen, National Taiwan Univ. (Taiwan)


Published in SPIE Proceedings Vol. 6914:
Medical Imaging 2008: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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