波谱学杂志2016，Vol.33Issue(4)：570-580,11.DOI:10.11938/cjmr20160406
基于GPU加速的磁共振血管造影图像的并行分割与追踪算法
Parallel Segmentation and Tracking Algorithm for Magnetic Resonance Angiography Images Based on GPU
摘要
Abstract
Clinical magnetic resonance angiography (MRA) often involves extraction of images, which is often done manually by radiologists. The process can be tedious and time-consuming. In this study, we propose a new parallel vessel segmentation/tracking algorithm, utilizing large-scale parallel computing provided by graphics processing unit (GPU). The whole three-dimensional image volumes are first divided into small cubes, which share surface with their neighbors. Each cube is then processed separately to determine whether there are vessels passing through its surface. These results are then used for global segmentation and vessel tracking. Application of the algorithm to real MRA data showed that segmentation of a whole-brain MRA dataset could be achieved in less than 1 s.关键词
磁共振成像(MRI)/血管造影/图像分割/图形处理器(GPU)/统一计算设备架构(CUDA)Key words
magnetic resonance imaging (MRI)/magnetic resonance angiography (MRA)/image segmentation/graphics processing unit (GPU)/compute unified device architecture (CUDA)分类
数理科学引用本文复制引用
张雪莹,王成龙,谢海滨,张成秀,马超,陆建平,杨光..基于GPU加速的磁共振血管造影图像的并行分割与追踪算法[J].波谱学杂志,2016,33(4):570-580,11.基金项目
国家高技术研究发展计划资助项目(2014AA123400)． （2014AA123400）
