Penczek Pawel A
Department of Biochemistry and Molecular Biology, The University of Texas Houston Medical School, 6431 Fannin, MSB6.218, Houston, TX 77030, USA.
J Struct Biol. 2002 Apr-May;138(1-2):34-46. doi: 10.1016/s1047-8477(02)00033-3.
A three-dimensional (3D) version of the spectral signal-to-noise ratio (SSNR)-based resolution measure is introduced. The measure is defined for a class of 3D reconstruction algorithms that use interpolation in Fourier space. The statistical properties of the SSNR are discussed and related to the properties of another resolution measure, the Fourier shell correlation (FSC). The new measure was tested on 3D structures calculated from a simulated set of quasi-evenly spaced 2D projections using a nearest-neighbor interpolation and a gridding algorithm. In the latter case, the results agree very well with the FSC-based estimate, with the exception of very high SSNR values. The main applicability of the 3D SSNR is tomography, where due to the small number of projections collected, FSC cannot be used. The new measure was applied to three sets of tomographic data. It was demonstrated that the measure is sufficiently sensitive to yield theoretically expected results. Therefore, the 3D SSNR opens up the possibility of evaluating the quality of tomographic reconstructions in an objective manner. The 3D distribution of SSNR is of major interest in single-particle analysis. It is shown that the new measure can be used to evaluate the anisotropy of 3D reconstructions. The distribution of SSNR is characterized by three anisotropy indices derived from principal axes of the 3D inertia covariance matrix of the SSNR. These indices are used to construct a 3D Fourier filter which, when applied to a 3D reconstruction of a macromolecule, maximizes the SNR in real space and minimizes real-space artifacts caused by uneven distribution of 2D projections.
引入了基于光谱信噪比（SSNR）的分辨率测量的三维（3D）版本。该测量是针对一类在傅里叶空间中使用插值的3D重建算法定义的。讨论了SSNR的统计特性，并将其与另一种分辨率测量方法——傅里叶壳相关（FSC）的特性相关联。使用最近邻插值和网格化算法，对从一组模拟的准均匀间隔二维投影计算得到的3D结构测试了这种新测量方法。在后一种情况下，除了非常高的SSNR值外，结果与基于FSC的估计非常吻合。3D SSNR的主要应用领域是断层扫描，在断层扫描中，由于收集的投影数量较少，无法使用FSC。将这种新测量方法应用于三组断层扫描数据。结果表明，该测量方法足够灵敏，能够产生理论上预期的结果。因此，3D SSNR为客观评估断层扫描重建质量提供了可能性。在单颗粒分析中，SSNR的三维分布是主要关注点。结果表明，这种新测量方法可用于评估3D重建的各向异性。SSNR的分布由从SSNR的三维惯性协方差矩阵的主轴导出的三个各向异性指数表征。这些指数用于构建一个三维傅里叶滤波器，当将其应用于大分子的三维重建时，可使实空间中的信噪比最大化，并最小化由二维投影不均匀分布引起的实空间伪影。
