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Cyst and Tumor Lesion Segmentation on Dental Panoramic Images using Active Contour Models

机译:囊肿和肿瘤病变在牙科全景图像上使用主动轮廓模型进行分割

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摘要

Active contours, or snakes, are computer-generated curves that move within images to find object boundaries. They are often used in computer vision and image analysis to detect and locate objects, and to describe their shape. Thus active contour can be used for object segmentation, especially the lesion in medical images. This paper presents the application of active contour models (Snakes) for the segmentation of lesions in dental panoramic image. The aim is to assist the clinical expert in locating potentially cyst or tumor cases for further analysis (e.g. classification of cyst or tumor lesion). In order to apply the snake formulation, color images were converted into gray images. Then, with correct parameters, we can create a snake that is attracted to edges or termination. Initializing contour, choosing parameter value and number of iteration affect the behaviour of the snake in a particular way. Using Receiver Pperating Characteristic (ROC), an average accuracy rate of 99.67 % is obtained. Examples of Snake segmentation results of lesions are presented.
机译:活动轮廓或蛇是计算机生成的曲线,可在图像内移动以查找对象边界。它们通常用于计算机视觉和图像分析以检测和定位对象,并描述它们的形状。因此,活性轮廓可用于对象分割,尤其是医学图像中的病变。本文介绍了主动轮廓模型(Snakes)在牙科全景图像中分割病变的应用。目的是协助临床专家定位潜在的囊肿或肿瘤病例进行进一步分析(例如,囊肿或肿瘤病变的分类)。为了应用蛇形制剂,将彩色图像转换成灰色图像。然后,使用正确的参数,我们可以创建被吸引到边缘或终止的蛇。初始化轮廓,选择参数值和迭代次数以特定方式影响蛇的行为。使用接收器观察特性(ROC),获得99.67%的平均精度率。提出了病变的蛇分段结果的实例。

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