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An automatic lesion detection method for dental x-ray images by segmentation using variational level set

机译:使用变分水平集的分段X射线图像自动病变检测方法

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Dental radiographs have been widely used by dentists in finding periodontal lesions or monitoring the progress of the periodontal defect treatment that is either impossible or difficult for human naked eyes. In this paper we propose a fully automatic gums lesion detection method for periapical dental X-ray images. The method includes two stages: (i) teeth- parts removing and (ii) lesion-region localization and severance labeling. In stage (i), morphological operations and histogram equalizations are first applied to enlarge the contrast between teeth and gums parts, then thresholding is used to separate the two types of regions. In stage (ii), gums-parts are first segmented into regions of normal, possible lesion or lesion, and serious lesion using a level set method with three coupled level set functions, and then the possible lesion or lesion region are further segmented into lesion and possible lesion regions using the same level set method. The experimental results demonstrate that our proposed method can detect and label all lesion regions in six periapical dental X-ray images which conform very well to human visual perception, and is robust to illumination variation to ± 30 intensity levels, as well.
机译:牙科射线照相已被牙医广泛地用于发现牙周病变或监测对于人的肉眼是不可能或困难的牙周缺损治疗的进展。在本文中,我们提出了一种用于根尖周牙X射线图像的全自动牙龈病变检测方法。该方法包括两个阶段:(i)去除牙齿部分和(ii)病变区域的定位和遣散标记。在阶段(i)中,首先应用形态学运算和直方图均衡化以扩大牙齿和牙龈部分之间的对比度,然后使用阈值分离两种类型的区域。在阶段(ii)中,首先使用具有三种耦合的水平设定功能的水平设定方法将牙龈部分划分为正常,可能的病变或病变以及严重病变的区域,然后将可能的病变或病变区域进一步划分为病变和可能的病变区域使用相同的水平集方法。实验结果表明,我们提出的方法可以检测和标记6个根尖周牙X射线图像中的所有病变区域,这些图像非常符合人类的视觉感知,并且对于±30强度水平的照明变化也具有较强的鲁棒性。

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