自适应加权全变分的低剂量CT统计迭代算法  

Statistical iterative algorithm based on adaptive weighted total variation for low-dose CT

作　　者：何琳[1] 张权[1] 上官宏[1] 张文[1] 张鹏程[1] 刘祎[1] 桂志国[1,2] 

机构地区：[1]电子测试技术国家重点实验室(中北大学),太原030051 [2]仪器科学与动态测试教育部重点实验室(中北大学),太原030051

出　　处：《计算机应用》2016年第10期2916-2921,共6页journal of Computer Applications

基　　金：国家自然科学基金资助项目(61271357);国家重大科学仪器设备开发专项(2014YQ24044508);山西省自然科学基金资助项目(2015011046);中北大学2013年校科学基金资助项目~~

摘　　要：针对低剂量计算机断层扫描(LDCT)重建图像时出现条形伪影和脉冲噪声的现象,提出一种自适应加权全变分的LDCT统计迭代重建算法。该算法克服了传统全变分(TV)算法在去除条形伪影的同时引入阶梯效应的缺点,把基于加权方差的加权因子与TV模型相结合提出自适应加权全变分模型,然后再把新模型应用到惩罚加权最小二乘(PWLS)重建算法中,这样就可以对图像的不同区域进行不同强度的去噪,从而取得噪声抑制和边缘保持的良好效果。采用Shepp-Logan模型和数字骨盆体模来验证算法的有效性,实验结果表明,所提算法的归一化均方距离和归一化平均绝对距离均比滤波反投影(FBP)、PWLS、惩罚加权最小二乘的中值先验(PWLS-MP)以及惩罚加权最小二乘的全变分(PWLS-TV)算法的值小,且可分别获得40.91 dB和42.25 dB的峰值信噪比。实验结果表明,该算法重建出的图像在有效去除条形伪影的同时对图像的边缘和细节起到很好的保护作用。Concerning the streak artifacts and impulse noise of the Low-Dose Computed Tomography （LDCT） reconstructed images, a statistical iterative reconstruction method based on adaptive weighted Total Variation （TV） for LDCT was presented. Considering the shortage that traditional TV may bring staircase effect while suppressing streak artifacts, an adaptive weighted TV model that combined the weighting factor based on weighted variation and TV model was proposed. Then, the new model was applied to the Penalized Weighted Least Square （PWLS）. Different areas of the image were processed with different de-noising intensities, so as to achieve a good effect of noise suppression and edge preservation. The Shepp-Logan model and the digital pelvis phantom were used to test the effectiveness of the proposed algorithm. Experimental results show that the proposed method has smaller Normalized Mean Square Distance （NMSD） and Normal Average Absolute Distance （NAAD） in the two experiment images, compared with the Filtered Back Projection （FBP）, PWLS, PWLS-Median Prior （PWLS-MP） and PWLS-TV algorithms. Meanwhile, the proposed method get Peak Signal-To-Noise Ratio （PSNR） of 40.91 dB and 42.25 dB respectively. Experimental results show that the proposed algorithm can well preserve image details and edges, while eliminating streak artifacts effectively.

关 键 词：低剂量计算机断层扫描 统计迭代重建 惩罚加权最小二乘 全变分 加权方差 

分 类 号：TP317.4[自动化与计算机技术—计算机软件与理论] TP301.6[自动化与计算机技术—计算机科学与技术]