Fig. 4.

Revised ARFS algorithm and determination of registration threshold. (A) ARFS workflow. The input is a 3D array of intensities with M height, N width, and T frames. Duplicate frames and frames which are lower outliers (µ-3σ) are rejected. Inter-frame motion is estimated in the “getMT” module by computing the phase correlation between frames. An empirically determined threshold was used to decide whether a phase correlation was sufficient to trust a registration. The phase correlation coefficient (PCC) is also used as a metric of intraframe distortion, and lower PCC outliers are rejected. Frames are then sorted into spatial clusters, refined, and the frames with the highest PCC per cluster are output. (B) Method for determining the aforementioned PCC threshold. Videos from isoeccentric locations were randomly interleaved, and the PCC between intra- and inter-video frame pairs were computed. (C-E) PCC threshold distributions for confocal, split-detector, and dark-field videos. The PCC threshold for each modality was defined as three standard deviations above the mean of all inter-video frame comparisons. This relatively conservative threshold increases the likelihood of false negatives (rejecting adequately registered frames), which is less deleterious for our purposes than false positives (accepting poorly registered frames). Distributions have worse separation for non-confocal modalities due to their lower SNR and contrast.