發(fā)布時(shí)間：2018-05-11 11:54

  本文選題：數(shù)字減影血管造影(DSA) + 雙邊濾波��； 參考：《河北大學(xué)》2017年碩士論文

【摘要】：近年來,心腦血管疾病發(fā)病率大幅增長,已經(jīng)成為人類健康的主要危害之一。因此,臨床醫(yī)學(xué)對(duì)血管類疾病的精確診斷提出了更高的要求,作為心腦血管疾病主要診斷方式的數(shù)字減影血管造影(DSA)是一種通過電子計(jì)算機(jī)進(jìn)行輔助常規(guī)血管造影成像的放射性治療方法,是臨床不可缺少的重要工具,然而,由于DSA成像特點(diǎn)和血管結(jié)構(gòu)的幾何復(fù)雜性,直接DSA成像帶有明顯的偽影,嚴(yán)重干擾臨床醫(yī)生對(duì)疾病的有效判斷,而現(xiàn)有的去偽影算法多通過圖像配準(zhǔn),這一過程損害了圖像的成像質(zhì)量,目前臨床中尚缺少對(duì)DSA序列圖像全自動(dòng)的去偽影增強(qiáng)算法�；谝陨吓R床問題,本文的主要工作如下:(1)設(shè)計(jì)了一種基于三邊濾波的去噪算法,并首次應(yīng)用在腦部DSA圖像,三邊濾波算法主要是雙邊濾波在原有的高斯距離權(quán)重和緊度權(quán)重外加入了“脈沖”權(quán)重的一種改進(jìn)算法,用來處理原本雙邊濾波器所無能為力的脈沖噪聲,同時(shí)又保存了雙邊濾波原來的保持圖像邊緣銳利的優(yōu)點(diǎn)。此算法可以方便有效地實(shí)現(xiàn)對(duì)高斯噪聲和脈沖噪聲去噪。(2)提出一種對(duì)腦部DSA序列圖像全自動(dòng)偽影去除和增強(qiáng)算法。既去除了單純?yōu)V波下腦部DSA留下的運(yùn)動(dòng)偽影,又彌補(bǔ)了傳統(tǒng)算法中因只做配準(zhǔn)再減影后圖像數(shù)據(jù)丟失導(dǎo)致對(duì)比度降低的不足,通過實(shí)驗(yàn)對(duì)比證明,本文方法不僅優(yōu)于醫(yī)院機(jī)器直接減影圖像和三邊濾波處理后的圖像,而且相比其他DSA血管增強(qiáng)算法,明顯提高了DSA圖像質(zhì)量,全自動(dòng)算法更加便捷了介入科醫(yī)生對(duì)病人的診斷和治療。(3)搭建針對(duì)介入科臨床應(yīng)用的用戶端平臺(tái),將以上開發(fā)的算法融入平臺(tái),并根據(jù)需求分析對(duì)系統(tǒng)進(jìn)行了整體框架設(shè)計(jì),整個(gè)系統(tǒng)平臺(tái)主要分為用戶模塊、顯示模塊、程序接口模塊、其他附屬功能模塊和疾病輔助診斷模塊幾部分功能模塊,經(jīng)過對(duì)系統(tǒng)調(diào)試,平臺(tái)的預(yù)期功能基本實(shí)現(xiàn)并且運(yùn)行穩(wěn)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.
【學(xué)位授予單位】：河北大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：R816.1;TP391.41

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