基于fBm模型和GLC矩阵的牙槽骨丢失区定位

P. Lin, P. Huang, P. Huang, H. Hsu, Ping Chen
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引用次数: 8

摘要

本文提出一种有效的牙尖周x线片检测牙槽骨丢失区域的方法。通过分析灰度共生矩阵(GLCM)或分形布朗运动(fBm)模型的h值测量的牙槽骨组织纹理,将x线片图像转换为骨纹理图像。然后通过自动阈值分割,将骨纹理图像分割为正常区域和骨质丢失区域。在6张根尖周图像上的实验结果表明,我们的方法使用fBm-H值作为纹理特征,在所有使用的特征中,可以从视觉和定量上检测出最符合牙医标记区域的骨质流失区域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Alveolar bone-loss area localization in periapical radiographs by texture analysis based on fBm model and GLC matrix
We propose an effective method to detect alveolar bone-loss areas in dental periapical radiographs in this paper. By analyzing the texture of alveolar bone tissues measured by Gray Level Co-occurrence Matrix (GLCM) or the H-value of fractal Brownian motions (fBm) model, we transfer radiograph images into bone-texture images. Then by auto-thresholding, we segment the bone-texture images into normal and bone-loss regions. Experimental results on six periapical images demonstrate that our method using fBm-H value as the texture feature can detect bone-loss areas best conforming to the areas marked by a dentist both visually and quantitatively among all the features used.
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