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. 2020 Dec 28;21(Suppl 21):534. doi: 10.1186/s12859-020-03885-9

Table 2.

The average similarity metric scores (SSIM) for the fully automated single-particle alignment

SSIM approach Similarity Time consuming
Default registration 99.648 2.19
Adjusted initial radius 99.754 2.06
Adjusted initial radius, maximum iterations 99.819 5.51
Similarity transformation model 99.561 5.16
Affine model based on similarity initial condition 99.627 5.10

Registration method 1 is based on the “default registration model” which registers the two particle images using affine transformation to solve the distortion between the two images includes scaling, rotation. Registration method 2 is based on the “adjusted initial radius model” which improves the particle image registration by adjusting the optimizer and metric configuration properties. Registration method3 is based on the “adjusted initial radius-based maximum iterations model” in which the optimizer controls the maximum number of iterations that the optimizer will be allowed to take. Also allows the registration search to run longer and potentially find better registration results. Registration method 4 is based on the “affine model-based on similarity initial condition model” which registers the particle images by using an “affine” transformation model with the “similarity” results used as an initial condition for the geometric transformation. This model is refined estimate for the registration includes the possibility of shear