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Detecting Bladder Abnormalities Based on Inter-layer Intensity Curve for Virtual Cystoscopy

机译:基于层间强度曲线的膀胱镜异常检测

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This paper presents a level set based method for bladder abnormality detection on Tl-weighted MR images. First, the bladder wall is segmented by using a coupled level set framework, in which the inner and outer borders of the bladder wall are extracted by two level set functions. Then, the middle layer of the bladder wall is founded and represented by a new level set function. Finally, the new level set function divides the bladder wall into several layers. The interlayer intensity of all voxels in each layer is sorted in ascending order to generate the inter-layer intensity curve. The results prove the effectiveness of inter-layer intensity curve in indicating the emerging of the bladder abnormalities.
机译:本文提出了一种基于水平集的T1加权MR图像膀胱异常检测方法。首先,通过使用耦合的水平集框架对膀胱壁进行分段,其中通过两个水平集函数提取膀胱壁的内边界和外边界。然后,建立膀胱壁的中间层并以新的水平设定功能表示。最后,新的水平设置功能将膀胱壁分为几层。将各层中所有体素的层间强度按升序排序,以生成层间强度曲线。结果证明了层间强度曲线在指示膀胱异常出现方面的有效性。

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