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Relative importance of the error sources in Wiener restoration of scintigrams

机译:错误源在闪烁图维纳复原中的相对重要性

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Through simulation studies, the relative importance of three error sources in Wiener filtering as applied to scintigrams is quantified. The importance of these error sources has been quantified using the percentage changed in squared error (compared to that of an image restored using an ideal Wiener filter) which is caused by estimating one of three factors in the Wiener filter. Estimating the noise power spectrum using the total image count produced to appreciable change in the squared error (less than 1%). Estimating the power spectrum of the true image from that of the degraded image produced small to moderate increases in the squared error (4-139%). In scintigraphic imaging, the modular transfer function (MTF) is dependent on source depth; hence, this study underscores the importance of using methods which reduce the depth dependence of the effective MTF prior to applying restoration filters. A novel method of estimating the power spectrum of the true image from that of the degraded images is also described and evaluated. Wiener restoration filters based on this spectral estimation method are found to be competitive with the image-dependent Metz restoration filter.
机译:通过仿真研究,量化了应用于闪烁图的维纳滤波中三个误差源的相对重要性。这些误差源的重要性已通过平方误差变化的百分比(与使用理想Wiener滤波器还原的图像的平方误差相比)进行了量化,该百分比误差是由估算Wiener滤波器中的三个因素之一引起的。使用针对平方误差的明显变化(小于1%)产生的总图像计数估算噪声功率谱。从退化图像的功率谱估计真实图像的功率谱会产生平方误差的小到中度增加(4-139%)。在闪烁成像中,模块化传递函数(MTF)取决于光源深度;因此,这项研究强调了在应用恢复滤波器之前使用降低有效MTF深度依赖的方法的重要性。还描述和评估了一种从退化图像的功率谱估计真实图像功率谱的新颖方法。发现基于这种频谱估计方法的维纳复原滤波器与依赖于图像的梅斯复原滤波器具有竞争力。

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