Iterative-based Partial Volume Effects correction with wavelet-based regularization for quantitative PET imaging
Iterative-based Partial Volume Effects correction with wavelet-based regularization for quantitative PET imaging
复制标题
基于迭代的部分体积效应校正和基于小波的正则化用于定量 PET 成像
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
M. Grégoire
中科院分区：
文献类型：
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作者：
A. Reilhac;W. Lehnert;Jianyu Lin;S. Meikle;M. Grégoire
阻碍动态PET成像定量测量的两个重要技术限制是：1）检测系统的有限空间分辨率，其由于部分容积效应而引起定量偏差; 2）单个时间帧中的不良计数统计，其进一步挑战后续动力学建模和分析。在这项工作中，我们提出了一个原始的方法恢复的动态PET图像，遭受了有限的空间分辨率和噪声过程的后果，这是基于加权最小二乘迭代反卷积的小波空间与时间正则化的小波系数。溶液图像显示出更少的噪声，发射结构之间更好的对比度，因此与没有校正的图像相比，应该允许更好的量化。
Two important technical limitations hampering quantitative measurements with dynamic PET imaging are 1) the limited spatial resolution of the detection system which induces quantitative biases due to Partial Volume Effects and 2), the poor counting statistics in the individual time frames which challenges further the subsequent kinetic modeling and analysis. In this work, we present an original method for the restoration of dynamic PET images that had suffered from both the consequences of the limited spatial resolution and the noise processes, which is based on the weighted least square iterative deconvolution in the wavelet space with temporal regularization of the wavelet coefficients. The solution image exhibits less noise, better contrasts between emitting structures and should therefore allow a better quantification compared with no correction‥