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Automatic Boundary Evolution Tracking via a Combined Level Set Method and Mesh Warping Technique: Application to Hydrocephalus

机译:通过组合级别集法和网眼翘曲技术自动边界演进跟踪:对脑积水的应用

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Hydrocephalus is a neurological disease which causes ventricular dilation due to abnormalities in the cerebrospinal fluid (CSF) circulation. Although treatment via a CSF shunt in the brain ventricles has been performed, poor rates of patient responses continue. Thus, to aid surgeons in hydrocephalus treatment planning, we propose a geometric computational approach for tracking hydrocephalus ventricular boundary evolution via the level set method and a mesh warping technique. In our previous work [1], we evolved the ventricular boundary in 2D CT images which required a backtracking line search for obtaining valid intermediate meshes. In this paper, we automatically detect the ventricular boundary evolution for 2D CT images. To help surgeons determine where to implant the shunt, we also compute the brain ventricle volume evolution for 3D MR images using our approach.
机译:脑积水是一种神经疾病,导致脑脊髓液(CSF)循环异常导致心室扩张。虽然已经进行了通过CSF分流的治疗已经进行了脑室,但患者反应的差异仍在继续。因此,为了帮助外科医生在脑积水治疗计划中,我们提出了一种通过水平集法和网眼翘曲技术提出了一种用于跟踪脑室脑室边界演化的几何计算方法。在我们以前的工作[1]中,我们在2D CT图像中进化了室外边界,其需要回溯线搜索以获得有效的中间网格。在本文中,我们自动检测2D CT图像的心室边界演进。为了帮助外科医生确定植入分流的地方,我们还使用我们的方法计算3D MR图像的脑室卷积演进。

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