Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/68882
標題: An improved GVF snake based breast region extrapolation scheme for digital mammograms
作者: Liu, C.C.
Tsai, C.Y.
Tsui, T.S.
Yu, S.S.
關鍵字: Breast
Mammogram
Extrapolation
GVF snake
Edge map adjusting
digitized mammograms
automatic detection
segmentation
masses
image
algorithm
border
nipple
期刊/報告no:: Expert Systems with Applications, Volume 39, Issue 4, Page(s) 4505-4510.
摘要: To accurately extrapolate the breast region from a mammogram is a crucial stage of breast mass analysis. It significantly influences the overall analysis accuracy and processing speed of the whole breast mass analysis. In this paper, a novel edge map adjusting gradient vector flow snake (EMA GVF snake) algorithm for extrapolation of breast region from mammograms is proposed. In the proposed algorithm, the median filter is used to filter out the noise in a mammogram, the scale down stage is used to resize down the mammogram size (hence speeding up the extrapolation). The binarization processing stage and the morphological erosion processing stage are used to find a rough breast border. Then a novel gradient adjusting stage is applied to get a modified edge map and the gradient vector flow snake (GVF snake) is used to get the accurate breast border from the rough breast border. The proposed algorithm is tested on 322 digital mammograms from the Mammogram Image Analysis Society database. The mean error function, misclassification error function and the relative foreground area error function are conducted to evaluate the results of the detected breast border and the extracted breast region. Experimental results show that the breast border extrapolated by the proposed algorithm approximately follows the breast border extrapolated by an expert radiologist. Experimental results also show that the proposed algorithm is more robust and precise than the traditional GVF snake scheme for the breast extrapolation on mammograms. (C) 2011 Elsevier Ltd. All rights reserved.
URI: http://hdl.handle.net/11455/68882
ISSN: 0957-4174
文章連結: http://dx.doi.org/10.1016/j.eswa.2011.09.136
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