Dehmeshki Jamshid, Ye Xujiong, Amin Hamdan, Abaei Maryam, Lin Xinyu, Qanadli Salah D
Medicsight plc, London, W1J 5AT, UK.
IEEE Trans Med Imaging. 2007 Mar;26(3):273-82. doi: 10.1109/TMI.2007.893344.
Coronary artery calcification (CAC) is quantified based on a computed tomography (CT) scan image. A calcified region is identified. Modified expectation maximization (MEM) of a statistical model for the calcified and background material is used to estimate the partial calcium content of the voxels. The algorithm limits the region over which MEM is performed. By using MEM, the statistical properties of the model are iteratively updated based on the calculated resultant calcium distribution from the previous iteration. The estimated statistical properties are used to generate a map of the partial calcium content in the calcified region. The volume of calcium in the calcified region is determined based on the map. The experimental results on a cardiac phantom, scanned 90 times using 15 different protocols, demonstrate that the proposed method is less sensitive to partial volume effect and noise, with average error of 9.5% (standard deviation (SD) of 5-7mm(3)) compared with 67% (SD of 3-20mm(3)) for conventional techniques. The high reproducibility of the proposed method for 35 patients, scanned twice using the same protocol at a minimum interval of 10 min, shows that the method provides 2-3 times lower interscan variation than conventional techniques.
冠状动脉钙化（CAC）是基于计算机断层扫描（CT）图像进行量化的。识别出钙化区域。使用针对钙化物质和背景物质的统计模型的修正期望最大化（MEM）方法来估计体素的部分钙含量。该算法限制了执行MEM的区域。通过使用MEM，基于上一次迭代计算得到的钙分布结果，对模型的统计特性进行迭代更新。利用估计的统计特性生成钙化区域内部分钙含量的图谱。根据该图谱确定钙化区域内的钙体积。在一个心脏模型上进行的实验结果表明，使用15种不同协议扫描90次，所提出的方法对部分容积效应和噪声的敏感性较低，平均误差为9.5%（标准差（SD）为5 - 7mm³），而传统技术的平均误差为67%（标准差为3 - 20mm³）。对于35名患者，使用相同协议至少间隔10分钟进行两次扫描，所提出方法的高重现性表明，该方法的扫描间变异比传统技术低2 - 3倍。
