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A Modified Distance Regularized Level Set Evolution for Masseter Segmentation

机译:改进的距离正则化水平集进化,用于咬肌分割

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Segmentation of the masseter muscle is one of the most important bases for diagnosis and treatment, but automatical segmentation of masseter is very difficult as the masseter and its adjacent tissues have very similar gray levels. In this paper, a novel method is presented to segment the masseter in MRI images, which modifies the distance regularized level set evolution (DRLSE) with a new adaptive edge indicator function. The presented method introduces the phase congruency into the edge indicator function and combines the image gradient with phase information together to solve the segmentation problem. The method is tested by 50 MR images of masseter muscle, and the results show it is an effective approach can be used to produce clinically acceptable results to this challenging work.
机译:咬肌的分割是诊断和治疗的最重要基础之一,但是由于咬肌及其邻近组织的灰度非常相似,因此自动分割咬肌非常困难。本文提出了一种在MRI图像中分割咬肌的新方法,该方法利用新的自适应边缘指示符功能修改了距离正则化水平集演化(DRLSE)。所提出的方法将相位一致性引入到边缘指示符函数中,并将图像梯度与相位信息结合在一起以解决分割问题。该方法通过咬肌的50幅MR图像进行了测试,结果表明,该方法可用于为这项具有挑战性的工作提供临床可接受的结果。

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