| 基于金字塔结构的乳腺肿块自动检测方法 |
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| 引用本文： | 徐晓燕,蔡畅,等.基于金字塔结构的乳腺肿块自动检测方法[J].上海生物医学工程,2002,23(2):8-11. |
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| 作者姓名： | 徐晓燕 蔡畅 |
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| 作者单位： | 上海大学通信与信息工程学院 200072
(徐晓燕，蔡畅)，上海大学通信与信息工程学院 200072(陈志宏) |
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| 摘 要： | 在乳腺图像中，肿块大多被埋没在复杂的，高密度的腺体背景中难以检测，针对这一问题，提出了一种基于金字塔结构的乳腺肿块自动检测方法。文中对几种典型的金字塔结构的构造方法做了比较。提出了一种使用BP人工神经网络用于实现低分辨率图像中肿块种子区域检测的新方法；提出了一种新的权值差别规则，同时添加了标志锥，使得生长算法不再严格受限于肿块种子的面积和形状，实验结果证明这种方法对于辅助临床医生诊断乳腺病变是有效的。
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| 关 键 词： | 乳腺肿块 金字塔结构 人工神经网络 自动识别 诊断 |
Auto-detection of Lesions in Digitized Mammograms based on Image Pyramid |
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| XU-Xiaoyan YAN-Zhuangzhi School of Communication and Information Engineering,Shanghai University Shanghai.Auto-detection of Lesions in Digitized Mammograms based on Image Pyramid[J].Shanghai Journal of Biomedical Engineering,2002,23(2):8-11. |
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| Authors: | XU-Xiaoyan YAN-Zhuangzhi School of Communication and Information Engineering Shanghai University Shanghai |
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| Abstract: | Lesions are usually difficult to detect as they often superimpose on dense structured background. In order to solve this problem, an approach of auto-detection of lesions based on image pyramid is presented in this paper. In the lower resolution image,a mass seed-region was detected by an ANN. With an improved grow tree algorithm, the edge of lesions was refined in the higher resolution image. A label pyramid is proposed in this method to make the tree grow method never restricted by area and shape of the seed-region. Experimental results show that the proposed approach is applicable to assist the radiologist's diagnosis. |
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| Keywords: | Image Pyramid Artificial Neural Network Auto-detection |
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