CUDA Based High Performance Adaptive 3D Voxel Growing for Lung CT Segmentation

摘要：

A novel CUDA based high performance parallel voxel growing algorithm to segment 3D CT pulmonary volumes with GPU Acceleration is introduced in this paper. The optimal parameters for segmentation is dynamically iterative adjusted based on the statistical information about previous segmented regions. To avoid the disadvantage of leaking during segmentation with the conventional voxel-growing based methods, it adopts a process to mutually utilize segment results between both of lateral lung leaves, which in turn benefits the discriminative segmentation on left and right lung leaves. Experiments show that the algorithms obtain accurate results with a speed about 10-20 times faster than the traditional methods on CPU, which imply that this algorithm is potentially valid for future clinical diagnosis applications.

作者: Weiming Zhai Fan Yang Yixu Song Yannan Zhao Hong Wang

作者单位: State Key Laboratory of Intelligent Technology and Systems Computer Science and Artificial Intelligence Research Devision Tsinghua National Laboratory for Information Science and Technology Department of Computer Science and Technology Tsinghua University, Beijing 100084, China

会议类型: 国际会议

会议名称: International Conference on Life System Modeling and Simulation,and International Conference on Intelligent Computing for Sustainable Energy and Environment(2010生命系统建模与仿真国际会议暨m2010可持续能源与环境智能计算国际会议)

会议地点: 无锡

会议语种:英文

页码: 10-18

在线出版日期: 2010-09-17（万方平台首次上网日期，不代表论文的发表时间）