Skip to main content

Table 1 Surrogate data parameters: a random Euclidean transformation determined by parameters (rsu) is applied to a set of n objects U to produce a new set of objects V. To simulate noise, p objects are added at random locations to both U and V

From: A random-sampling approach to track cell divisions in time-lapse fluorescence microscopy

Param Description
\(\varepsilon\) Minimum object separation
n Number of points to generate in the point-set U
p Number of “noise” points to add to the point-set U and the point-set V
r Generate random (global) rotations in the range [\(-\pi /r\), \(\pi /r\)]
s Generate random (global) translations in the range [0, s]
u Random uniform shift of points in V on each axis in the range [0, u]