脑部DSA去伪影增强算法的研究及实现
本文选题:数字减影血管造影(DSA) + 双边滤波 ; 参考:《河北大学》2017年硕士论文
【摘要】:近年来,心脑血管疾病发病率大幅增长,已经成为人类健康的主要危害之一。因此,临床医学对血管类疾病的精确诊断提出了更高的要求,作为心脑血管疾病主要诊断方式的数字减影血管造影(DSA)是一种通过电子计算机进行辅助常规血管造影成像的放射性治疗方法,是临床不可缺少的重要工具,然而,由于DSA成像特点和血管结构的几何复杂性,直接DSA成像带有明显的伪影,严重干扰临床医生对疾病的有效判断,而现有的去伪影算法多通过图像配准,这一过程损害了图像的成像质量,目前临床中尚缺少对DSA序列图像全自动的去伪影增强算法。基于以上临床问题,本文的主要工作如下:(1)设计了一种基于三边滤波的去噪算法,并首次应用在脑部DSA图像,三边滤波算法主要是双边滤波在原有的高斯距离权重和紧度权重外加入了“脉冲”权重的一种改进算法,用来处理原本双边滤波器所无能为力的脉冲噪声,同时又保存了双边滤波原来的保持图像边缘锐利的优点。此算法可以方便有效地实现对高斯噪声和脉冲噪声去噪。(2)提出一种对脑部DSA序列图像全自动伪影去除和增强算法。既去除了单纯滤波下脑部DSA留下的运动伪影,又弥补了传统算法中因只做配准再减影后图像数据丢失导致对比度降低的不足,通过实验对比证明,本文方法不仅优于医院机器直接减影图像和三边滤波处理后的图像,而且相比其他DSA血管增强算法,明显提高了DSA图像质量,全自动算法更加便捷了介入科医生对病人的诊断和治疗。(3)搭建针对介入科临床应用的用户端平台,将以上开发的算法融入平台,并根据需求分析对系统进行了整体框架设计,整个系统平台主要分为用户模块、显示模块、程序接口模块、其他附属功能模块和疾病辅助诊断模块几部分功能模块,经过对系统调试,平台的预期功能基本实现并且运行稳定。
[Abstract]:In recent years, the incidence of cardiovascular and cerebrovascular diseases has increased dramatically, and has become one of the main hazards to human health. Therefore, clinical medicine has put forward higher requirements for accurate diagnosis of vascular diseases. Digital subtraction angiography (DSAs), as the main diagnostic method of cardiovascular and cerebrovascular diseases, is a kind of radiotherapeutic method which can be used to assist conventional angiography imaging by computer, and is an indispensable and important tool in clinic. Because of the characteristics of DSA imaging and the geometric complexity of vascular structure, direct DSA imaging has obvious artifacts, which seriously interferes with the effective judgment of diseases by clinicians. However, most of the existing de-artifact algorithms are based on image registration. This process damages the image quality, and there is still a lack of full automatic de-artifact enhancement algorithm for DSA sequence images. Based on the above clinical problems, the main work of this paper is as follows: (1) A denoising algorithm based on trilateral filtering is designed and applied to brain DSA image for the first time. The trilateral filtering algorithm is mainly an improved algorithm of adding "pulse" weight to the original Gao Si distance weight and tightness weight, which is used to deal with the impulse noise which can not be done by the two-sided filter. At the same time, the advantage of bilateral filtering is preserved to keep the edge sharp. This algorithm is convenient and effective for Gao Si noise and pulse noise denoising. 2) A full automatic artifact removal and enhancement algorithm for brain DSA images is proposed. It not only removes the motion artifacts left by the DSA of the brain under pure filtering, but also makes up for the deficiency of the traditional algorithm, which is caused by the loss of image data after only registration and subtraction. This method is not only superior to the direct subtraction image of hospital machine and the image processed by trilateral filtering, but also can improve the quality of DSA image obviously compared with other DSA vascular enhancement algorithms. The automatic algorithm makes it more convenient for interventional doctors to diagnose and treat patients. It builds a client platform for clinical application of interventional department, integrates the above developed algorithms into the platform, and designs the overall framework of the system according to the needs analysis. The whole system platform is mainly divided into user module, display module, program interface module, other auxiliary function module and disease assistant diagnosis module. After debugging the system, The expected functions of the platform are basically implemented and run stably.
【学位授予单位】:河北大学
【学位级别】:硕士
【学位授予年份】:2017
【分类号】:R816.1;TP391.41
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