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Segmentation of the bladder wall using coupled level set methods

机译:使用耦合水平集方法对膀胱壁进行分割

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We describe a novel method to segment the bladder wall in magnetic resonance imaging (MRI) to support the detection of disease, such as endometriosis, and for surgical planning. We segment the inner and outer wall boundary using T2- and T1-weighted MRI images, respectively. A new coupling technique for level sets is formulated and tested on 54 T2- and T1-weighted image pairs. A local phase based dimensionless feature asymmetry measurement using the monogenic signal is used. The results are validated against manual segmentations using the Dice similarity coefficient. Our findings show that the coupling significantly improves the segmentation by preventing leakage due to weak image features and MR bias field. This method shows promising potential for other segmentation tasks involving thin, elongated structures.
机译:我们描述了一种在磁共振成像(MRI)中分割膀胱壁的新方法,以支持疾病(例如子宫内膜异位症)的检测以及手术计划。我们分别使用T2和T1加权MRI图像分割内壁和外壁边界。制定了一套新的水平集耦合技术,并在54个T2和T1加权图像对上进行了测试。使用基于单相信号的基于局部相位的无量纲特征不对称性测量。使用Dice相似系数针对手动分割验证了结果。我们的发现表明,这种耦合通过防止由于弱图像特征和MR偏置场引起的泄漏而显着改善了分割效果。该方法显示了用于其他细分任务的潜在潜力,这些细分任务涉及到细长的结构。

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