GPU-Accelerated Interactive Visualization and Planning of Neurosurgical Interventions
GPU-Accelerated Interactive Visualization and Planning of Neurosurgical Interventions
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DOI：
10.1109/mcg.2013.35
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发表时间：
2014-01-01
影响因子：
1.8
通讯作者：
Deng, Zhigang
中科院分区：
文献类型：
--
作者：
Rincon-Nigro, Mario;Navkar, Nikhil V.;Deng, Zhigang
计算方法和硬件平台的进步为手术规划提供了医学成像数据集的有效处理。对于采用直线进入路径的神经外科干预，计划需要选择从头皮到目标区域的路径，这对患者的风险最小。提出了一种GPU加速的方法，它利用加速空间数据结构和在GPU上有效实现算法，可以交互式地定量估计特定路径的风险。在其计算效率和可扩展性的评估，它实现了互动率，即使是高分辨率的网格。一项用户研究和神经外科医生的反馈确定了该方法在术前计划和术中重新计划方面的潜在受益。
Advances in computational methods and hardware platforms provide efficient processing of medical-imaging datasets for surgical planning. For neurosurgical interventions employing a straight access path, planning entails selecting a path from the scalp to the target area that's of minimal risk to the patient. A proposed GPU-accelerated method enables interactive quantitative estimation of the risk for a particular path. It exploits acceleration spatial data structures and efficient implementation of algorithms on GPUs. In evaluations of its computational efficiency and scalability, it achieved interactive rates even for high-resolution meshes. A user study and feedback from neurosurgeons identified this methods' potential benefits for preoperative planning and intraoperative replanning.