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Alveolar bone-loss area localization in periapical radiographs by texture analysis based on fBm model and GLC matrix

机译:基于FBM模型和GLC矩阵的纹理分析,通过纹理分析造成局部射射线照相中的肺泡骨质损失区域化

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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.
机译:我们提出了一种有效的方法,可以在本文中检测牙齿局部射线照片中的肺泡骨质损失区域。通过分析通过灰度共发生矩阵(GLCM)或分形褐色运动(FBM)模型的H值测量的肺泡骨组织的质地,我们将射线照片图像转移到骨骼纹理图像中。然后通过自动阈值化,我们将骨骼纹理图像分段为正常和骨丢失区域。六种同图像上的实验结果表明,我们使用FBM-H值的方法,因为纹理特征可以检测最能符合牙本士标记的区域,在视觉上和定量地符合牙医的区域。

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