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基于自动图形的人工耳蜗电极在CT中的定位

Automatic graph-based localization of cochlear implant electrodes in CT.

作者信息

Noble Jack H, Dawant Benoit M

机构信息

Dept. of Elect. Eng. and Comp. Sci., Vanderbilt University, Nashville, TN USA.

出版信息

Med Image Comput Comput Assist Interv. 2015 Oct;9350:152-159. doi: 10.1007/978-3-319-24571-3_19. Epub 2015 Nov 20.

Abstract

Cochlear Implants (CIs) restore hearing using an electrode array that is surgically implanted into the cochlea. Research has indicated there is a link between electrode location within the cochlea and hearing outcomes, however, comprehensive analysis of this phenomenon has not been possible because techniques proposed for locating electrodes only work for specific implant models or are too labor intensive to be applied on large datasets. We present a general and automatic graph-based method for localizing electrode arrays in CTs that is effective for various implant models. It relies on a novel algorithm for finding an optimal path of fixed length in a graph and achieves maximum localization errors that are sub-voxel. These results indicate that our methods could be used on a large scale to study the link between electrode placement and outcome across electrode array types, which could lead to advances that improve hearing outcomes for CI users.

摘要

人工耳蜗(CIs)通过手术植入耳蜗的电极阵列来恢复听力。研究表明,耳蜗内电极位置与听力结果之间存在联系,然而,由于所提出的电极定位技术仅适用于特定的植入模型,或者应用于大型数据集时劳动强度太大,因此无法对这一现象进行全面分析。我们提出了一种基于图的通用自动方法,用于在CT中定位电极阵列,该方法对各种植入模型都有效。它依赖于一种新颖的算法,用于在图中找到固定长度的最优路径,并实现亚体素级的最大定位误差。这些结果表明,我们的方法可大规模用于研究不同电极阵列类型的电极放置与结果之间的联系,这可能会带来改善人工耳蜗使用者听力结果的进展。

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