The FindFoci plugins allow the identification of peak intensity regions within 2D and 3D images. The algorithm is highly configurable and parameters can be optimised using reference images and then applied to multiple images using the batch mode.

Details of the benefits of training an algorithm on multiple images can be found in the FindFoci paper:

Herbert AD, Carr AM, Hoffmann E (2014) FindFoci: A Focus Detection Algorithm with Automated Parameter Training That Closely Matches Human Assignments, Reduces Human Inconsistencies and Increases Speed of Analysis. PLoS ONE 9(12): e114749. doi: 10.1371/journal.pone.0114749.

Latest Updates

August 2016: Added supported for 32-bit images and multi-threaded batch processing.

ImageJ Plugins

There are several different plugins that can be run from the ImageJ plugins menu:

Find Foci A standard ImageJ plugin filter that operates on an opened image. Results are presented as a mask image, shown in tabular format and/or saved to file
FindFoci GUI Opens a permanent window frame within ImageJ and allows selection of different images. It runs the FindFoci plugin to perform the processing work. A preview option allows the parameters to be interactively updated
FindFoci Batch Allows a set of parameters for the FindFoci algorithm to be applied to all the images in a directory. The algorithm is run on each image in turn and the results are saved to an output directory
FindFoci Optimiser Finds the best parameters for the FindFoci algorithm using the maxima marked on a representative image. It iterates through thousands of combinations and identifies the best parameters to find the desired peak regions. These parameters can then be easily applied to other images of the same type using the ImageJ scripting tools or the FindFoci Batch plugin
FindFoci Optimiser GUI A convenience plugin that provides an ImageJ window with a selection list of all images available for the FindFoci Optimiser
FindFoci Optimiser Multi-Image Allows the FindFoci Optimiser to be run on a directory of reference images to find the best parameters across the dataset. The results for each image are saved to an output directory and can be reloaded allowing the parameters to be ranked using different scoring methods
FindFoci Helper An interactive plugin that aligns the manually added point Regions of Interest (ROIs) with the peaks found by the FindFoci algorithm. The plugin intercepts user clicks with the multi-point ROI tool and assigns the marked points to the closest/highest peak within a search radius
FindFoci Settings Configure settings for the FindFoci algorithm, e.g. the limit on the number of potential maxima for the FindFoci algorithm.
FindFoci Match Calculator Allows two sets of FindFoci results to be compared. The FindFoci analysis must have been saved to memory using the 'Save to memory' option.
FindFoci Macro Extensions Registers functions that can be used in the ImageJ macro language.

Full details of the FindFoci plugins can be found in the FindFoci User Manual.

Download the plugin.

Additional Plugins

Several additional plugins use the FindFoci algorithms to provide analysis functionality for images containing points.

Match Calculator Computes the match statistics between two images marked with point ROIs. This uses the same match scores as the FindFoci Optimiser: Number of matchs; True positives; False positives; False negatives; Jaccard; Precision; Recall; and F-score. It can be used to compare the peak identification performed by two methods, including manual assignment
Point Extractor ImageJ plugin that saves the marked multi-point Regions of Interest (ROIs) of an image to file
Point Aligner ImageJ plugin that aligns the marked multi-point Regions of Interest (ROIs) of an image with the peaks found by the FindFoci algorithm. Foci are aligned using an uphill gradient to the parent maxima.
Spot Distance Detects spots within a mask/ROI region. The mask can define multiple regions using a different pixel value for each. Outputs a table of spot positions and a summary table of the number of spots with min/max/average distances.

Spots are detected using the maxima within a Difference of Gaussians image. The Smoothing parameter controls the removal of image noise. The Feature Size parameter controls the expected size of the spots; contrast changes (edges) much larger than the Feature Size will be removed from the image. (Set the Feature Size to zero to disable the Difference of Guassians; spots will be detected using peaks on the smoothed image.) Optionally spots can be removed if they fail a circularity threshold.

Provides options to process the current frame or all frames in the stack. The last identified spots can be shown on the image as an overlay. The region counter is incremented for each run of the plugin allowing regions to be separated in the results
Spot Pairs ImageJ plugin that analyses marked ROI points in an image. Find the closest pairs within a set distance of each other. Supports a preview of the pairs and saves results to a table
Mask Segregator Overlay a mask on an image and segregate into two classes. For each unique pixel value in the mask (defining an object), obtain the mean pixel value of the object and then segregate the objects into two classes, either by auto-thresholding or interactively.
Mask Analyze Particles... Extend the ImageJ Particle Analyser to allow the particles to be obtained using contiguous pixels with a unique value. If blank pixels exist between two pixels with the same value then they will be treated as separate objects.

This plugin works is useful on masks where each object region has a unique value, for example the output mask created by FindFoci.
Spot Density Calculate the density around spots defined using FindFoci results loaded from memory. Only spots within a mask region are processed. Any foci within the maximum analysis distance from the edge are excluded from analysis. Analysis is performed in 2D only.

Outputs histograms of the closest distances between spots and the density of particles around the spots (i.e. the Pair Correlation function).
Mask Object Dimensions Identify the inertia tensor (principle rotation axes around the centre-of-mass) for each object and computes the minimum and maximum pixel along each axis that is inside the object. Draws the axes on the image and produces a results table. Can be used to estimate dimensions of objects in 2/3D. The plugin works best on objects that are spherical.

Objects are identified using unique pixel values (can be non-contiguous), for example the output mask created by FindFoci.
Assign Foci to Objects Finds objects in an image using contiguous pixels of the same value. Locates the closest object to each FindFoci result held in memory and summarises the counts. Analysis is performed in 2D only.
Assign Foci to Clusters Performs 2D clustering on the latest FindFoci results held in memory. Optionally can draw the clusters on the Find Foci output mask if this is selected when the plugin is run.
Translocation Finder Find translocations using markers for colocalisation using 3 FindFoci results sets stored in memory. Find triplets where the two markers from channel 2 & 3 matching a foci in channel 1 are also a matching pair. Output a guess for a translocation where channel 13 distance << 12|23, no transolcation where 12 << 13|23.
Spot Radial Intensity Output the radial intensity around spots within a mask region. Spots are defined using FindFoci results held in memory.
Spot Pair Distance Output the distances between the pair of spots from two channels at a user selected position. Functions using a plugin action tool added to the ImageJ toolbar.
Object Foci Depth Finds objects in an image using contiguous pixels of the same value. Computes the distance of each foci inside an object to the edge/surface (the foci depth).

For further details on GDSC ImageJ plugins please contact Alex Herbert.