Image Analysis

(Last updated 14th May 2013 with 'Export Movies from Multi-point Time-Lapse')

A number of dedicated offline image analysis workstations are available to process and analyse images obtained on our imaging equipment.

Help and guidance to the best analysis approaches, plus the development of analysis protocols are available from the facility through discussion with the facility manager.

Software Packages

Image J (site)

FIJI Image J (site)

Imaris (Bitplane site)

Zen Light Edition 2009 FREE file viewer (Download - 89mb file)

Cell Profiler (site)

leeds bioimaging

Human endothelial cell labelled for endosomes (red) and nuclear DNA (blue). Endosomes highlighted with 'Spots' module in Imaris (grey) to enable counting and size classification.

 

Software Training Workshops

To be announced...

 

Example image analysis procedures

Nuclear counting using ImageJ

A common task is cell counting, and this can be performed in mammalian cells with a nuclear counterstain called DAPI. DAPI labels double stranded DNA and highlights the position of each nucleus with high specificity. In the example below of HeLa cells DAPI labelled nuclei are counted with a ImageJ macro. The procedure the macro uses is to initially remove background on the image with a Gaussian blur. After this the image is segmented with a thresholding algorithm (Moments) to highlight areas occupied by the nuclei and remove regions in the background (black nuclei). This B&W image is then processed to identify each individual nucleus and the output is a count. This approach can also be used to generate analysis 'masks' which can be placed over the original image in order to quantify data and determine, for example, mean fluorescence intensity of total intensity on individual nuclei.

Please contact the facility manager if you are interested in performing this type of analysis on your images.

leeds bioimaging

Original DAPI stained image > Gaussian blur to remove background > Threshold > Output showing nuclear outlines

 

Protocols

Export movies from multi-point timelapse (Confocal protocol)