冠狀動(dòng)脈系統(tǒng)CT圖像去噪研究
本文選題:冠狀動(dòng)脈系統(tǒng) + 計(jì)算機(jī)斷層圖像; 參考:《天津工業(yè)大學(xué)》2017年碩士論文
【摘要】:在冠狀動(dòng)脈醫(yī)學(xué)影像診斷領(lǐng)域中,低劑量計(jì)算機(jī)斷層掃描技術(shù)(Low Dose Computed Tomography,LDCT)受到越來(lái)越多的學(xué)者和醫(yī)學(xué)研究人員的關(guān)注。但是,劑量降低會(huì)伴隨著的心臟重建圖像退化,影響臨床診斷。因此,在保證冠狀動(dòng)脈CT成像質(zhì)量的同時(shí)又減少有害的輻射劑量具有重要的科學(xué)意義和應(yīng)用前景。本文研究偏微分方程方法在冠狀動(dòng)脈系統(tǒng)低劑量CT圖像去噪中的應(yīng)用。在各向異性擴(kuò)散模型基礎(chǔ)上,提出了改進(jìn)的4鄰域偏微分降噪算法。針對(duì)PM模型的病態(tài)性,利用中值濾波后的冠狀動(dòng)脈投影圖像代替原始圖像梯度模值,并根據(jù)局部區(qū)域內(nèi)各擴(kuò)散方向的相鄰像素的相關(guān)度差異性定義了歸一權(quán)梯度函數(shù),得到PMG模型,從而有效地實(shí)現(xiàn)噪聲快速平滑和斷層圖像中冠狀動(dòng)脈分支細(xì)節(jié)的較好保留;考慮到冠狀動(dòng)脈投影圖像在各階段的統(tǒng)計(jì)特性變化規(guī)律和傳統(tǒng)擴(kuò)散門限選取困難的情況,應(yīng)用當(dāng)前鄰域內(nèi)梯度的絕對(duì)偏差均值計(jì)算圖像的梯度門限值,并定義了時(shí)變擴(kuò)散函數(shù),得到PMC模型。該模型能夠自適應(yīng)調(diào)節(jié)噪聲平滑和血管走支保留之間的平衡;將PMG模型與PMC模型進(jìn)行融合,得到PMGC模型,以進(jìn)一步提高降噪算法處理后的冠狀動(dòng)脈圖像質(zhì)量水平。最后,計(jì)算機(jī)仿真和冠狀動(dòng)脈CT掃描數(shù)據(jù)實(shí)驗(yàn)結(jié)果顯示,改進(jìn)算法能夠獲得更高質(zhì)量的重建圖像,并具有較好的運(yùn)算效率,為臨床分析提供了有效的數(shù)據(jù)支持。
[Abstract]:In the field of coronary artery medical imaging diagnosis, low Dose Computed tomography (LDCT) has attracted more and more scholars and medical researchers' attention. However, dose reduction can be associated with cardiac reconstruction image degradation, affecting clinical diagnosis. Therefore, it has important scientific significance and application prospect to ensure the quality of coronary artery CT imaging while reducing the harmful radiation dose. In this paper, the application of partial differential equation method in low dose CT image denoising of coronary artery system is studied. Based on the anisotropic diffusion model, an improved 4-neighborhood partial differential denoising algorithm is proposed. In view of the ill-condition of PM model, the coronary artery projection image after median filtering is used to replace the original image gradient, and the normalized weight gradient function is defined according to the difference of the correlation degree of adjacent pixels in each diffusion direction in the local region. The PMG model is obtained, which can effectively smooth the noise and preserve the details of coronary artery branch in the image. Considering the variation of the statistical characteristics of coronary artery projection images in various stages and the difficulty in selecting the traditional diffusion threshold, the gradient threshold value of the image is calculated by using the absolute deviation mean of the gradient in the current neighborhood, and the time-varying diffusion function is defined. The PMC model is obtained. The model can adaptively adjust the balance between noise smoothing and vascular branch retention, and fuse PMG model with PMC model to obtain PMGC model, so as to further improve the image quality of coronary artery after noise reduction algorithm. Finally, computer simulation and coronary artery CT scan data experiment results show that the improved algorithm can obtain higher quality reconstruction images, and has a better computational efficiency, which provides an effective data support for clinical analysis.
【學(xué)位授予單位】:天津工業(yè)大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類號(hào)】:R541.4;R816.2;TP391.41
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