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SEEG Trajectory Planning: Combining Stability, Structure and Scale in Vessel Extraction

机译:SEEG轨迹规划:在船只提取中结合稳定性,结构和规模

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StereoEEG implantation is performed in patients with epilepsy to determine the site of the seizure onset zone. Intracranial haemorrhage is the most common complication associated to implantation carrying a risk that ranges from 0.6 to 2.7%, with significant associated morbidity. SEEG planning is done pre-operatively to identify avascular trajectories for the electrodes. In current practice neurosur-geons have no assistance in the planning of the electrode trajectories. There is great interest in developing computer assisted planning systems that can optimize the safety profile of electrode trajectories, maximizing the distance to critical brain structures. In this work, we address the problem of blood vessel extraction for SEEG trajectory planning. The proposed method exploits the availability of multi-modal images within a trajectory planning system to formulate a vessel extraction framework that combines the scale and the neighbouring structure of an object. We validated the proposed method in twelve multi-modal patient image sets. The mean Dice similarity coefficient (DSC) was 0.88±0.03, representing a statistically significantly improvement when compared to the semi-automated single rater, single modality segmentation protocol used in current practice (DSC=0.78±0.02).
机译:在癫痫患者中进行StereoEEG植入,以确定癫痫发作区的位置。颅内出血是与植入相关的最常见并发症,风险范围为0.6%至2.7%,并伴有明显的发病率。 SEEG计划在术前完成,以识别电极的无血管轨迹。在当前的实践中,神经素在电极轨迹的规划中没有帮助。开发计算机辅助计划系统引起了极大的兴趣,该系统可以优化电极轨迹的安全性,最大程度地延长至关键脑部结构的距离。在这项工作中,我们解决了SEEG轨迹规划中血管提取的问题。所提出的方法利用轨迹规划系统中多模式图像的可用性来制定结合了对象的比例尺和邻近结构的血管提取框架。我们在十二种多模式患者图像集中验证了该方法。平均Dice相似系数(DSC)为0.88±0.03,与当前实践中使用的半自动单评分者,单模式细分方案相比,具有统计学上的显着提高(DSC = 0.78±0.02)。

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