本文選題：低劑量CT + 迭代重建�。� 參考：《南方醫(yī)科大學(xué)學(xué)報(bào)》2015年03期

【摘要】：目的研究兩種不同的Huber正則化閾值自適應(yīng)選取方法及其在低劑量CT迭代重建中的應(yīng)用。方法針對(duì)低劑量CT重建采用基于Huber正則化的迭代重建技術(shù),Huber正則化閾值的選取分別基于全局和局部邊緣保持算子。結(jié)果仿真數(shù)據(jù)的實(shí)驗(yàn)結(jié)果表明,兩類Huber正則化閾值自適應(yīng)選取方法均能較好地抑制重建圖像中的噪聲和偽影。結(jié)論兩類Huber正則化閾值自適應(yīng)選擇方法均可實(shí)現(xiàn)低劑量CT優(yōu)質(zhì)重建。
[Abstract]:Objective to study two adaptive Huber regularization threshold selection methods and their applications in low dose CT iterative reconstruction. Methods for low-dose CT reconstruction, the iterative reconstruction technique based on Huber regularization was used to select the threshold of Huber regularization based on global and local edge preserving operators, respectively. Results the experimental results of simulation data show that both Huber regularization threshold adaptive selection methods can suppress the noise and artifact in the reconstructed image. Conclusion two kinds of Huber regularization threshold adaptive selection methods can achieve high quality reconstruction of low dose CT.
【作者單位】： 南方醫(yī)科大學(xué)生物醫(yī)學(xué)工程學(xué)院;
【基金】：國家自然科學(xué)基金(81101046,81371544) 國家973重點(diǎn)基礎(chǔ)研究發(fā)展計(jì)劃(2010CB732503) 國家科技支撐計(jì)劃(2011BAI12B03)~~
【分類號(hào)】：R814.2
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本文編號(hào)：1811744