Image classification

Import ROI from a zip file produced with ImageJ's ROI manager. Works as a standalone plugin and as a block for Protocols

This segmentation method performs a N-class thresholding based on a K-Means classification of the image histogram, then extracts objects in a bottom-up manner using user-defined minimum and maximum object sizes. Very useful to detect clustered objects in fluorescence microscopy.

Identifies dead worms based on a couple of parameters. 

This plugin calculates a classification based on the histogram of the image by generalizing the IsoData algorithm to more than two classes.

This plugin works on 8-bit and 16-bit grayscale images only.