SpotFinderF if a simplified version of SpotFinderZ designed to work in the absence of cell data. This function provides only partial functionality and is included on experimantal basis. The purpose of this tool is detecting spots with subpixel resolution on images without cells.

SpotFinderF uses most of the parameters of SpotFinderZ, which have the same meaning. There is, however, no training tool. The training can be performed with SpotFinderZ or done manually. The most sensitive parameter is "Min. height", which has to be reduced to detect more spots. The acceptable level can be obtained by displaying the results after processing.

The program can normalize the data by dividing the intensity by the average intensity in the current frame (if "Frame" normalization is selected) or in the whole set of frames (if "Stack" normalization is selected). The output can be performed either to a file (if "File" is selected) or to MATLAB's workspace (if "Screen" is selected).

Output format

The output variable is called spotList and is a hierarchical MATLAB's cell array. It is an array of frames, each being an array of spots, each being a structure of fields describing one spot in one frame. Each such structure has the format similar to the output format of SpotFinderZ. Namely, the structure has the following fields:

  • x - euclidian coordinate from the left of the image.

  • y - euclidian coordinate from the top of the image.

  • m - magnitude (brightness) of the spots (combined brightness under the Gaussian fit excluding background).

  • h - height of the spots (one of the Gaussian fit parameters).

  • w - width of the spots (one of the Gaussian fit parameters).

  • b - background under the spots (one of the Gaussian fit parameters).

Displaying results

To visualize the results, use the dispcellall function:

   images = loadimageseries('your_folder_with_images');

Replace your_folder_with_images with the folder name where the images are and replace the number 1 in the second line to the number of the frame you would like to display.

Outputting data to Excell

To save the results in Excel format, use the exportspots2xls function:


The program will ask you for the output file name. The data is saved as a table with eight columns: the frame number, the spot number and the six characteristics of the spots (the same and in the same order as above).


This example demonstrates how to perform the analysis and display the data using an image of individual Cy5 fluorophores immobilized on a glass coverslip (courtesy of Dr. Sangjin Kim).

1. Start MATLAB. Set the working path in MATLAB to the folder of the example: ...\MicrobeTracker...\examples\spotfinder2 (see the image below, click on the image for its full resolution version).

Setting the working path in MATLAB

1a. This step is optional. It you want to see the raw data, load the images into the workspace. Type in MATLAB's command window:

   images = loadimageseries('spotfinderf');

and use MATLAB's imshow command (for the first image in the stack if the file is a multipage TIFF):


SpotFinderF program

2. To start SpotFinderF, type in MATLAB's command window:


SpotFinderF program

3. Select Spots checkbox on the Output panel. Screen checkbox gets automatically selected, which means that the data will appear in MATLAB's workspace. Click on Params and then Load to load the parameters from spotfinderf.sfp file. Click OK to close the parameters window.

4. Press Run to start SpotFinderF. Select spotfinderf folder for the images. Because you are not outputting data to a file, no file is requested. Now the program will display a progress bar and perform processing for about a minute. When it is done, spotList variable will appear in the workspace.

5. Now let's display the images with the detected spots. If you skip the 1a step and the images have not been loaded, load them now:

   images = loadimageseries('spotfinderf');

Now run dispcellall tool:


Displayed spots

6. It also possible use various display options of the dispcellall tool, for example to display the spots as yellow circles:

   dispcellall(spotList,images,1,[],[],[],4,[1 1 0],'circle')

Displayed spots

For an example of testing the Shift limit parameter using the same data set, see the example for testspotprecision function.