面向脑血管物联网电子健康平台的分割及重构关键技术研究

Key Technologies of Vessel Segmentation and Reconstruction of the Cerebrovascular Disease Detection E-Health Platform Based on the Internet of Things

在物联网应用中,脑血管诊疗的电子健康平台可以很好地实现脑血管健康异地保健和远程医疗的要求.设计实现了脑血管诊疗的物联网e-health平台层次结构.面对物联网平台网络的普及化应用要求,提出并实现了基于统计模型的脑血管无人工干预分割算法;面向物联网平台组件之间的快速和高可靠性数据传输特点,提出并实现了基于球B样条三维重构模型.基于双高斯模型的脑血管统计分割模型融合改进的SEM算法,无需人工设定初始轮廓、高维进化函数和进化终止条件.脑血管在脑组织中所占比例较低(<5%),成像灰度不均匀,形态复杂且个体差异性大,该方法可获得良好的分割效果.球B样条模型具有严格的数学基础、较小的数据规模、平稳的光滑连续性和良好的交互性,非常适宜在物联网平台上传输.在上述关键技术的基础上,研究实现了光线投射法的GPUCUDA的并行加速体绘制及三维虚拟环境下脑血管的交互漫游和自主漫游.系统可实现脑血管疾病的诊断、医疗方案的制定和治疗过程中的监测以及脑血管疾病的教学和培训.相关研究为物联网平台下精细组织电子健康发展作出了有益的尝试.

In the application of Internet of things （IoT）, the cerebrovascular disease detection e-health platform can realize the long care and long telemedicine of cerebrovascular health. The four levels architecture of the platform is designed and realized in the paper. The segmentation and reconstruction of brain vessel is deeply researched here. The double Gauss mixture model is put forward to realize the cerebrovascular segmentation and the stochastic estimation maximization （SEM） algorithm is adopted to estimate the parameters of it. It could be easily used for the common user of the platform without initial contour, high dimensional evolution equation and the iteration terminal condition. The cerebrovascular vessels have low proportion （〈5%） in the brain tissue. Its angiography gray is nonuniform. Geometry is complex and individual differences are quite large. The segmentation method in our paper can get the good result. Ball B-Spline curve （BBSC） has the characters of strict mathematic foundation, less dataset, stable smoothness and continuity, good interactivity. It suits to transfer the data in the IoT platform. Combing these technologies, a CUDA （compute unified device architecture） based ray-casting volume rendering, the interactive and automatic virtual wandering are realized. The platform can realize the diagnosis of the cerebrovascular disease, the medical plan design and monitor in the treatment, which can also be widely used in the teaching. The research is an interesting try to extend the fine tissues e-health platform based on the internet of things.