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Calculation of lung-heart ratios for single-photon emission computed tomography

机译:单光子发射计算机断层扫描的肺心率计算

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The authors investigate the effectiveness of simple iterative reconstruction techniques in calculating lung-heart activity ratios (LHRs). The LHR has been shown to be an effective indicator of the severity of coronary artery disease in cardiac SPECT. A study was conducted with a mathematical cardiac torso phantom that modelled uptake of /sup 201/Tl in the heart and lung regions. The projection data included only the effects of nonuniform photon attenuation. The data were first reconstructed with zeroth-order Chang and a variant of the Bellini method, both of which utilize from the nonuniform attenuation map. This (NU) Bellini method compensates exactly for attenuation in the heart region, but is incorrect for other regions in the medium. These reconstructions were then used as the initial estimates in the iterative Chang, variable step-size (VSS) Chang, and Morozumi methods, for 1 and 5 iterations. The average heart count (AHC) and average lung count (ALC) were calculated using region-of-interest (ROI) templates derived from the true activity map. The population mean LHR was tabulated as the ratio of the ALC to AHC. Using the same reconstruction procedure, the authors also calculated the sample mean LHR and standard deviation from 21 noisy 3D reconstructions. The results showed that the NU Bellini and zeroth-order Chang methods provided good estimates of the AHC, while both estimated the ALC poorly. The NU Bellini method yielded a negative ALC, while the zeroth-order Chang method estimated the ALC at twice its true value. Application of 1 iteration of Chang can correct for the negative bias in the ALC for the NU Bellini estimate, and can correct for the positive bias in the ALC for the zeroth-order Chang estimate, while retaining a low bias in the AHCs for the two methods. Thus more precise LHRs are produced. Furthermore, the sample standard deviation of the LHR estimate was shown to be small in both of these cases.
机译:作者研究了简单的迭代重建技术在计算肺心活动率(LHR)方面的有效性。 LHR已被证明是心脏SPECT中冠状动脉疾病严重程度的有效指标。对数学上的心脏躯干体模进行了研究,该模型模拟了心脏和肺区域对/ sup 201 / T1的摄取。投影数据仅包括非均匀光子衰减的影响。首先使用零阶Chang和Bellini方法的一种变体来重建数据,这两者均从非均匀衰减图中使用。这种(NU)Bellini方法可以准确补偿心脏区域的衰减,但对于介质中的其他区域则不正确。然后将这些重构用作迭代Chang,可变步长(VSS)Chang和Morozumi方法的初始估计,分别进行1次和5次迭代。平均心脏计数(AHC)和平均肺部计数(ALC)使用从真实活动图得出的感兴趣区域(ROI)模板进行计算。将人口平均LHR列表为ALC与AHC的比率。使用相同的重建程序,作者还从21个嘈杂的3D重建中计算了样本平均LHR和标准差。结果表明,NU Bellini方法和零阶Chang方法对AHC的估计很好,而对ALC的估计却很差。 NU Bellini方法得出的ALC为负,而零阶Chang方法估计的ALC为真实值的两倍。 Chang的1次迭代的应用可以校正NU Bellini估计的ALC中的负偏差,并且可以校正零阶Chang估计的ALC中的正偏差,同时保持两个AHC的低偏差。方法。因此产生了更精确的LHR。此外,在这两种情况下,LHR估计值的样本标准偏差均较小。

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