首页> 外文会议>International Conference on Medical Image Computing and Computer-Assisted Intervention(MICCAI 2005) pt.1; 20051026-29; Palm Spring,CA(US) >Cross Validation of Experts Versus Registration Methods for Target Localization in Deep Brain Stimulation
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Cross Validation of Experts Versus Registration Methods for Target Localization in Deep Brain Stimulation

机译:交叉验证专家与注册方法在深部脑刺激中的目标定位

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In the last five years, Deep Brain Stimulation (DBS) has become the most popular and effective surgical technique for the treatment of Parkinson's disease (PD). The Subthalamic Nucleus (STN) is the usual target involved when applying DBS. Unfortunately, the STN is in general not visible in common medical imaging modalities. Therefore, atlas-based segmentation is commonly considered to locate it in the images. In this paper, we propose a scheme that allows both, to perform a comparison between different registration algorithms and to evaluate their ability to locate the STN automatically. Using this scheme we can evaluate the expert variability against the error of the algorithms and we demonstrate that automatic STN location is possible and as accurate as the methods currently used.
机译:在过去的五年中,深部脑刺激(DBS)已成为治疗帕金森氏病(PD)的最流行和最有效的手术技术。丘脑底核(STN)是应用DBS时通常涉及的目标。不幸的是,STN通常在常见的医学成像模式中不可见。因此,通常考虑使用基于图集的分割来将其定位在图像中。在本文中,我们提出了一种方案,该方案允许两者在不同的注册算法之间进行比较,并评估它们自动定位STN的能力。使用此方案,我们可以针对算法的误差评估专家的可变性,并且证明自动STN定位是可能的,并且与当前使用的方法一样准确。

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