Auto Segment Channel

This is an auto segmentation algorithm using the work of: Padmanabhan, K., W.F. Eddy, and J.C. Crowley, A novel algorithm for optimal image thresholding of biological data. J Neurosci Methods, 2010. 193(2): p. 380-4. both memory efficient and fast, this routine uses the MCT (Maximum Correlation Thresholding) algorithm over the histogram. This means that even large data-sets can be done with minimal time. Although passing b/t Imaris and matlab can take some time. There are some built-in decision trees for data sets with multiple possible thresholds. This application is ideal for time series as each time point is segmented independently allowing for an adaptive threshold through time. This is useful for handling bleaching. for data sets that are noisy or low signal to noise (i.e. spinning disk, spim, lsfm...) I would advise using the Gaussian filter in Imaris before running this extension. executable for Windows only