Fluorescence microscopy

Histogram-based background subtractor for ImageJ.

The implemented algorithm is based on the assumption that, compared to the background region, object (foreground) regions are small. The plugin builds local histograms and assumes the most occuring intensity to be part of the background.

Three different methods for correcting fluorescence bleaching. 1. Simple (framewise ratio based) 2. Exponential (curve fitting with exponential decay model) 3. Histogram matching (register histogram shape. with 16 bit, it takes long time... it should be improved).

The track manager enables the use of DSP-like trackProcessors. This can affect the display of tracks, selection in time or by ROIs, and also compute some views like the overlaid and animated local flow graph, polar graph.

A TrackProcessor that allows the user to monitor, visualize, and export, the intensity profile of tracks in time lapse sequences of 2D images.

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.