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首页> 外文会议>IEEE International Symposium on Biomedical Imaging >Localization Of Cochlear Implant Electrodes From Cone Beam Computed Tomography Using Particle Belief Propagation
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Localization Of Cochlear Implant Electrodes From Cone Beam Computed Tomography Using Particle Belief Propagation

机译：使用粒子信仰传播，来自锥形光束的扳手植入电极的定位

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摘要

Cochlear implants (CIs) are implantable medical devices that can restore the hearing sense of people suffering from profound hearing loss. The CI uses a set of electrode contacts placed inside the cochlea to stimulate the auditory nerve with current pulses. The exact location of these electrodes may be an important parameter to improve and predict the performance with these devices. Currently the methods used in clinics to characterize the geometry of the cochlea as well as to estimate the electrode positions are manual, error-prone and time consuming.We propose a Markov random field (MRF) model for CI electrode localization for cone beam computed tomography (CBCT) data-sets. Intensity and shape of electrodes are included as prior knowledge as well as distance and angles between contacts. MRF inference is based on slice sampling particle belief propagation and guided by several heuristics. A stochastic search finds the best maximum a posteriori estimation among sampled MRF realizations.We evaluate our algorithm on synthetic and real CBCT data-sets and compare its performance with two state of the art algorithms. An increase of localization precision up to 31.5% (mean), or 48.6% (median) respectively, on real CBCT data-sets is shown.
机译：耳蜗植入物（CIS）是可植入的医疗器械，可以恢复患有深刻听力损失的人的听力感。 CI使用放置在耳蜗内的一组电极触点，以刺激电流脉冲的听觉神经。这些电极的确切位置可以是改善和预测这些设备的重要参数。目前，诊所中使用的方法来表征耳蜗的几何形状以及估计电极位置是手动，容易出错和耗时的.We提出了用于CI电极定位的Markov随机场（MRF）模型，用于锥形光束计算机断层扫描（CBCT）数据集。作为现有知识以及触点之间的距离和角度包括电极的强度和形状。 MRF推断基于切片采样粒子信仰传播，并以几种启发式引导。随机搜索在采样MRF实现中找到了最大的后验估计。我们在合成和真实CBCT数据集中评估我们的算法，并将其具有本领域的两个状态的性能进行比较。显示了在实际CBCT数据集上的定位精度高达31.5％（平均值）或48.6％（中位数）的增加。

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