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首页> 外文期刊>Journal of Biomedical Science and Engineering >Comparative Analysis of Adaptive Vessel Segmentation—Cerebral Arteriovenous Malformation
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Comparative Analysis of Adaptive Vessel Segmentation—Cerebral Arteriovenous Malformation

机译：自适应性血管分割与脑动静脉畸形的比较分析

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Aim: Neurovascular abnormalities are extremely complex, due to the multitude of factors acting simultaneously on cerebral hemodynamics. Cerebral Arteriovenous Malformation (CAVM) hemo-dynamic in one of the vascular abnormality condition results changes in the vessels structures and hemodynamics in blood vessels. The challenge is segmenting accurate vessel region to measure hemodynamics of CAVM patients. The clinical procedure is in-vivo method to measure hemodynamics. The catheter-based procedure is difficult, as it is sometimes difficult to reach vessels sub-structures. Methods: In this paper, we have proposed adaptive vessel segmentation based on threshold technique for CAVM patients. We have compared different adaptive methods for vessel segmentation of CAVM structures. The sub-structures are modeled using lumped model to measure hemodynamics non-invasively. Results: Twenty-three CAVM patients with 150 different vessel locations of DSA datasets were studied as part of the adaptive segmentation. 30 simulated data has been evaluated for more than 150 vessels locations for sub-segmentation of vessels. The segmentation results are evaluated with accuracy of 93%. The computed p-value is smaller than the significance level 0.05. Conclusion: The adaptive segmentation using threshold based produces accurate vessel segmentation, results in better accuracy of hemodynamic measurements for DSA images for CAVM patients. The proposed adaptive segmentation helps clinicians to measure hemodynamic non-invasively for the segmented sub-structures of vessels.
机译：目的：由于多种因素同时作用于脑血流动力学，神经血管异常异常复杂。脑动静脉畸形（CAVM）在一种血管异常情况下的血流动力学导致血管结构的变化和血管的血流动力学。面临的挑战是分割准确的血管区域以测量CAVM患者的血液动力学。临床过程是体内方法以测量血液动力学。基于导管的手术比较困难，因为有时很难到达血管的亚结构。方法：在本文中，我们提出了基于阈值技术的CAVM患者自适应血管分割方法。我们比较了CAVM结构的血管分割的不同自适应方法。使用集总模型对子结构进行建模，以非侵入性地测量血液动力学。结果：作为适应性分割的一部分，研究了23个具有150个不同血管位置的DSA数据集的CAVM患者。已对150多个位置的船只进行了细分，评估了30个模拟数据。分割结果的评估精度为93％。计算出的p值小于显着性水平0.05。结论：基于阈值的自适应分割可产生准确的血管分割，从而为CAVM患者的DSA图像提供更好的血液动力学测量准确性。拟议的自适应分割可帮助临床医生无创地测量血管的分割亚结构的血流动力学。

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