Institute of Computing Technology and Key Lab of Intelligent Information Processing, Chinese Academy of Sciences, Beijing 100190, China.
J Struct Biol. 2011 Sep;175(3):277-87. doi: 10.1016/j.jsb.2011.06.002. Epub 2011 Jun 15.
Three-dimensional (3D) reconstruction of electron tomography (ET) has emerged as an important technique in analyzing structures of complex biological samples. However most of existing reconstruction methods are not suitable for extremely noisy and incomplete data conditions. We present an adaptive simultaneous algebraic reconstruction technique (ASART) in which a modified multilevel access scheme and an adaptive relaxation parameter adjustment method are developed to improve the quality of the reconstructed 3D structure. The reconstruction process is facilitated by using a column-sum substitution approach. This modified multilevel access scheme is adopted to arrange the order of projections so as to minimize the correlations between consecutive views within a limited angle range. In the adaptive relaxation parameter adjustment method, not only the weight matrix (as in the existing methods) but the gray levels of the pixels are employed to adjust the relaxation parameters so that the quality of the reconstruction is improved while the convergence process of the reconstruction is accelerated. In the column-sum substitution approach, the computation to obtain the reciprocal of the sum for the columns in each view is avoided so that the needed computations for each iteration can be reduced. Experimental results show that the proposed technique ASART is better based on objective quality measures than other methods, especially when data is noisy and limited in tilt angles. At the same time, the reconstruction by ASART outperforms that of simultaneous algebraic reconstruction technique (SART) in speed.
三维(3D)重建电子断层扫描(ET)已成为分析复杂生物样本结构的重要技术。然而,大多数现有的重建方法都不适合非常嘈杂和不完整的数据条件。我们提出了一种自适应同时代数重建技术(ASART),其中开发了一种改进的多级访问方案和一种自适应弛豫参数调整方法,以提高重建 3D 结构的质量。通过使用列和替换方法来简化重建过程。这种改进的多级访问方案用于安排投影的顺序,以在有限的角度范围内最小化连续视图之间的相关性。在自适应弛豫参数调整方法中,不仅使用权重矩阵(如现有方法中),而且还使用像素的灰度级来调整弛豫参数,从而在提高重建质量的同时加速重建的收敛过程。在列和替换方法中,避免了获取每个视图中列的和的倒数的计算,从而减少了每个迭代所需的计算量。实验结果表明,所提出的技术 ASART 在基于客观质量度量的方面优于其他方法,特别是在数据嘈杂和倾斜角度有限的情况下。同时,ASART 的重建速度优于同时代数重建技术(SART)。