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机构地区:[1]北京理工大学光电学院北京市混合现实与新型显示工程技术研究中心,北京100081
出 处:《计算机辅助设计与图形学学报》2014年第2期217-224,共8页Journal of Computer-Aided Design & Computer Graphics
基 金:国家"九七三"重点基础研究发展计划项目(2010CB732505);"十二五"国家科技支撑计划(2013BAI01B01);国家"八六三"高技术研究发展计划(2013AA010803);广东省中国科学院全面战略合作项目(2011B090300079)
摘 要:针对临床超声图像中人体组织的清晰度和辨识度较低,病灶及其周围组织的相对关系难于观测的问题,提出一种基于CT体数据的超声图像实时模拟方法.首先针对血液在超声图像中存在的多普勒现象建立多尺度响应函数,实现管状结构的检测与增强;然后提出一种超声邻域差值比重方法,实现对单换能器反射系数和噪声的模拟;最后通过离散窗函数实现对多换能器图像的调制与融合.实验结果表明,该方法可实现对任意视角超声图像的逼真模拟,处理速度达20帧/s,可应用于临床超声图像的培训过程.Ultrasound has been widely used for diagnosis in clinical practice. However, as the contrast of ultrasound image is usually low, the abnormal tissue is hard to be discriminated from the normal anatomic structures. Hence, in this paper, a novel ultrasound simulation method based on CT image is proposed for the training purpose of the ultrasound image recognition. First, a multi-scale method is developed to enhance vascular tree structures to simulate the Doppler phenomenon of ultrasound; Second, reflection parameter of a single transducer element with speckle noise is calculated by the weighted integration of adjacent regions on the ultrasound propagation path in the CT images. Third, a discrete window function is employed to produce integration and fusion effects of multiple transducer elements. Experimental results show that realistic ultrasounds can be generated at any imaging angle from CT image. And the simulation speed reaches 20fps, which can be used for ultrasound training procedures in clinical practices.
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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