Pectoral Muscle Segmentation in Mammograms Based on Anatomic Features
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摘要: 提出了基于解剖学特征(纹理特征和形状特征)的乳腺X线图像胸肌区域分割方法. 融合边缘信息到谱聚类算法得到过分割图像. 根据区域的亮度分布和胸肌的三角形状特征,提出区域聚合算法, 从过分割图像中识别出胸肌边缘.该方法在322幅mini-MIAS (Mammographic image analysis society)乳腺图像和50幅北京大学人民医院乳腺中心乳腺图像上进行验证, 实验结果表明,该方法对不同大小、形状和亮度的胸肌分割具有较强的鲁棒性.Abstract: In this paper, an anatomic features-based method is proposed to segment the pectoral muscle region according to texture feature and shape feature. Firstly, spectral clustering combined with edge information is presented and used to segment the pectoral muscle, leading to an over-segmented result. Afterwards, a region merging algorithm is proposed on the basis of the intensity distribution of regions and the characteristic of triangle shape. Finally, the pectoral muscle is identified from the over-segmented result according to region merging. The proposed method is evaluated on 322 mammograms from the mammographic image analysis society (mini-MIAS) database and 50 mammograms from the Breast Center of Peking University People's Hospital (BCPKUPH). The results show that the proposed method works well for pectoral muscles of different sizes, shapes and intensities.
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Key words:
- Image segmentation /
- mammograms /
- pectoral muscle /
- region merging /
- spectral clustering
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