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Spectral signal-to-noise ratio and resolution assessment of 3D reconstructions

机译:光谱信噪比和3D重建的分辨率评估

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摘要

Measuring the quality of three-dimensional (3D) reconstructed biological macromolecules by transmission electron microscopy is still an open problem. In this article, we extend the applicability of the spectral signal-to-noise ratio (SSNR) to the evaluation of 3D volumes reconstructed with any reconstruction algorithm. The basis of the method is to measure the consistency between the data and a corresponding set of reprojections computed for the reconstructed 3D map. The idiosyncrasies of the reconstruction algorithm are taken explicitly into account by performing a noise-only reconstruction. This results in the definition of a 3D SSNR which provides an objective indicator of the quality of the 3D reconstruction. Furthermore, the information to build the SSNR can be used to produce a volumetric SSNR (VSSNR). Our method overcomes the need to divide the data set in two. It also provides a direct measure of the performance of the reconstruction algorithm itself; this latter information is typically not available with the standard resolution methods which are primarily focused on reproducibility alone.
机译:通过透射电子显微镜测量三维(3D)重建的生物大分子的质量仍然是一个悬而未决的问题。在本文中,我们将频谱信噪比(SSNR)的适用性扩展到使用任何重建算法重建的3D体积的评估。该方法的基础是测量数据与为重建的3D地图计算的一组相应的重投影之间的一致性。通过执行仅噪声的重建,显式考虑了重建算法的特质。这导致了3D SSNR的定义,该定义提供了3D重建质量的客观指标。此外,用于建立SSNR的信息可用于产生体积SSNR(VSSNR)。我们的方法克服了将数据集一分为二的需要。它还提供了重建算法本身性能的直接度量;后者的信息通常无法通过标准分辨率方法获得,这些方法主要关注可重复性。

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