GPU并行计算在医学光声成像中的应用  

Application of GPU Parallel Computing in Medical Photoacoustic Imaging

作　　者：益新尧 孟静[1] 司广涛[1] 朱晓瑜 

机构地区：[1]信息科学与工程学院曲阜师范大学,山东省日照市276826

出　　处：《电子技术（上海）》2017年第11期79-82,共4页Electronic Technology

摘　　要：光声成像因其兼具纯光学成像的高对比度和超声成像的高空间分辨率,已经成为生物医学成像领域的研究热点之一。目前,光声成像技术已被证明在癌症和心血管疾病的研究和诊断中具有重要的应用价值。然而,光声成像中的大数据量采集和大规模的信号处理过程限制了光声成像速度,直接影响到该成像技术在疾病实时监测等领域的应用。GPU并行计算提供了便捷、有效的高速数据处理框架,在信号处理领域得到了广泛的应用,其为快速光声成像的实现提供了一条有效的途径。本文综述了目前GPU并行计算在光声成像中的应用方法和领域,阐述了GPU并行计算在加速光声成像过程中的有效性,对下一步GPU和光声成像的深入融合研究提供了有价值的参考。Featured by high contrast of optical imaging and high spatial resolution of ultrasonic imaging, photoacoustic imaging has become one of the hotspots in the field of biomedical imaging. At present, it has been proven that the photoacoustic imaging technology has important application value in research and diagnosis of cancer and cardiovascular disease. However, large-volume data collection and large-scale signal processing in photoacoustic imaging limit the speed of photoacoustic imaging, which directly affects its application in situations such as real-time monitoring of diseases. GPU（graphic processing unit） parallel computing, which has been widely used in the field of signal processing, provides a data processing framework characterized by convenience, effectiveness and high-speed, as well as an effective way to realize fast photoacoustic imaging. This paper firstly summarizes the major application methods and researches on GPU parallel computing in photoacoustic imaging, then explains the effectiveness of GPU parallel computing in accelerating photoacoustic imaging, and finally provides valuable implications to studies on the integration of GPU and photoacoustic imaging in the future.

关 键 词：GPU并行计算 医学光声图像 实时显示 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]