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Contrast Adaptive Total p-norm Variation Minimization Approach to CT reconstruction for Artifact Reduction in Reduced-view Brain Perfusion CT

机译:对比度自适应总P-NAR规范变化最小化方法对减少视图脑灌注CT的CT重建CT

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Perfusion CT (PCT) examinations are getting more frequently used for diagnosis of acute brain diseases such as hemorrhage and infarction, because the functional map images it produces such as regional cerebral blood flow (rCBF), regional cerebral blood volume (rCBV), and mean transit time (MTT) may provide critical information in the emergency work-up of patient care. However, a typical PCT scans the same slices several tens of times after injection of contrast agent, which leads to much increased radiation dose and is inevitability of growing concern for radiation-induced cancer risk. Reducing the number of views in projection in combination of TV minimization reconstruction technique is being regarded as an option for radiation reduction. However, reconstruction artifacts due to insufficient number of X-ray projections become problematic especially when high contrast enhancement signals are present or patient's motion occurred. In this study, we present a novel reconstruction technique using contrast-adaptive TpV minimization that can reduce reconstruction artifacts effectively by using different p-norms in high contrast and low contrast objects. In the proposed method, high contrast components are first reconstructed using thresholded projection data and low p-norm total variation to reflect sparseness in both projection and reconstruction spaces. Next, projection data are modified to contain only low contrast objects by creating projection data of reconstructed high contrast components and subtracting them from original projection data. Then, the low contrast projection data are reconstructed by using relatively high p-norm TV minimization technique, and are combined with the reconstructed high contrast component images to produce final reconstructed images. The proposed algorithm was applied to numerical phantom and a clinical data set of brain PCT exam, and the resultant images were compared with those using filtered back projection (FBP) and conventional TV reconstruction algorithm. Our results show the potential of the proposed algorithm for image quality improvement, which in turn may lead to dose reduction.
机译:灌注CT(PCT)考试越来越经常用于诊断出血和梗塞等急性脑病,因为其产生的功能映射图像如区域脑血流(RCBF),区域脑血容量(RCBV),以及平均值运输时间(MTT)可以在患者护理的紧急处理中提供关键信息。然而,典型的PCT在注射造影剂后扫描相同的切片几十次,这导致辐射剂量大大增加,并且不可避免地对辐射诱导的癌症风险产生巨大的关注。在电视最小化重建技术组合中减少投影中的视图数量被认为是辐射减少的选择。然而,由于存在高对比度增强信号或发生患者的运动,因此由于存在高对比度增强信号或者发生患者的运动而导致的重建伪影变得有问题。在这项研究中,我们通过使用高对比度和低对比度物体的不同p-norms,使用对比度自适应TPV最小化的新型重建技术,其可以减少重建伪像。在所提出的方法中,首先使用阈值投影数据和低p范数总变化来重建高对比度分量,以反映两个投影和重建空间中的稀疏性。接下来,修改投影数据通过创建重建的高对比度分量的投影数据并从原始投影数据中减去它们的投影数据来包含低对比度对象。然后,通过使用相对高的P-NORM电视最小化技术来重建低对比度投影数据,并且与重建的高对比度分量图像组合以产生最终重建图像。将所提出的算法应用于数值幻像和脑PCT检查的临床数据集,并将所得图像与使用过滤后投影(FBP)和传统电视重建算法进行比较。我们的结果表明,所提出的图像质量改善算法的潜力,这又可能导致剂量减少。

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