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Thyroid nodule segmentation using active contour bilateral filtering on ultrasound images

机译:使用主动轮廓双侧滤波对超声图像进行甲状腺结节分割

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Utilization of ultrasound imaging with various resolutions as modalities for thyroid nodules examination is growing rapidly. This is consistent with an increase in incidence of thyroid malignancy. Thyroid ultrasound examination is considered superior to other medical imaging modalities for its non-invasive, practical, inexpensive and painless. In the examination process, a radiologist expects areas of thyroid nodules that can be localized precisely from the surrounding normal tissue. Thus boundary of the nodules can be seen as to be regular or irregular. Boundary is one of the important features of malignancy that doctors use to make a diagnosis. Most malignant nodules have unclear and irregular boundaries. Imprecise segmentation result will lead to misdiagnosis based on boundary characteristics. Active contour segmentation technique is applied for detecting boundary of thyroid nodules and separating them with normal tissue iteratively. However, the characteristics of the ultrasound image that brings speckle noises make the segmentation process more complicated. It also resulted in interpretation errors and inaccuracies diagnosis made by a doctor. The intricacy of irregular nodule area can not easily be solved by changing the value of iteration on active contour. Therefore, speckle noise reduction method is needed to overcome this problem so that nodule area segmented properly. In this paper speckle noise reduction is done with bilateral filter. Comparison of image segmentation results of thyroid nodules with and without bilateral filter is attached at the end of this article. The combination of bilateral filter and active contour showed better results with the edge of the nodules firmly and clear.
机译:各种分辨率的超声成像作为甲状腺结节检查的手段正在迅速发展。这与甲状腺恶性肿瘤发病率增加相一致。甲状腺超声检查因其无创,实用,廉价和无痛性而被认为优于其他医学成像方式。在检查过程中,放射科医生期望可以从周围正常组织中精确定位出甲状腺结节区域。因此,结节的边界可以看作是规则的或不规则的。边界是医生用来诊断的恶性肿瘤的重要特征之一。大多数恶性结节边界不清晰且不规则。分割结果不准确将导致基于边界特征的误诊。主动轮廓分割技术用于检测甲状腺结节的边界,并与正常组织进行迭代分离。然而,带来斑点噪声的超声图像的特征使得分割过程更加复杂。这也导致了医生的解释错误和不准确的诊断。通过改变活动轮廓上的迭代值,不容易解决不规则结节区域的复杂性。因此,需要减少斑点噪声的方法来克服该问题,从而使结节区域适当地分割。在本文中,斑点噪声的减少是通过双边滤波器完成的。本文结尾处附有和不附有双边滤镜的甲状腺结节图像分割结果的比较。双侧过滤器和活动轮廓的结合显示出更好的效果,结节边缘牢固而清晰。

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