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机构地区:[1]清华大学医学院生物医学工程系,北京100084
出 处:《中国生物医学工程学报》2014年第2期178-185,共8页Chinese Journal of Biomedical Engineering
基 金:国家自然科学基金(81127003;51361130032);清华大学自主科研计划
摘 要:在超声引导下的介入治疗等应用中,利用三维定位系统跟踪超声成像平面的位置和姿态,从而定位病灶位置。对超声探头与定位系统的传感器间的空间变换关系进行标定,是影响整体系统精度的重要环节。广泛应用的基于N线模型的标定方法要求手工拾取超声图像中亮斑标志点的坐标并识别其对应的N线组编号。传统的人工点选方法容易引入主观定位误差和编号错误,且耗时较长。对此,提出一种预测标志点位置、在其邻域进行搜索、确定N形目标点坐标和编号的自动标定方法,以提高探头标定的精度和效率。实验表明,新方法与传统方法相比,精密度从1.57 mm提高到0.63 mm,标定误差从2.66 mm降低到1.80 mm;处理每帧图像所需的平均时间为0.067 s,节省大量人工操作的时间,并保证标定的精度。In the ultrasound guided intervention, the imaging plane is tracked using a 3D spatial tracking device, hence it is necessary to determine the transform between the ultrasound probe and the attached position sensor by calibration. The accuracy of calibration has significant impacts on the overall accuracy of ultrasound guidance. The widely used calibration method based on N-phantom requires extracting fidueial points manually in ultrasound images. The conventional manual approach is prone to subjective pick-up errors and mistakes in labeling as well as time-consuming. In this paper, an automatic method, which searches and identifies N- fidueials based on position prediction, is presented. Experimental results showed that the proposed method improves calibration precision to 0. 63 mm and accuracy to 1.80 mm, compared to 1.57 mm and 2.66 mm of the conventional method, respectively. The average processing time on each frame is 0. 067 s, which is much less than that of manual processing.
分 类 号:R318[医药卫生—生物医学工程]
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