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Pancreas++

The microscopic image analysis of pancreatic Islet of Langerhans morphology is crucial for the investigation of diabetes and metabolic diseases. Besides the general size of the islet, the percentage and relative position of glucagon-containing alpha-, and insulin-containing beta-cells is also important for pathophysiological analyses, especially in rodents. Hence, the ability to identify, quantify and spatially locate peripheral and ‘involuted’ alpha-cells in the islet core is an important analytical goal.

Pancreas++ is a novel algorithm that facilitates the fully-automated, non-biased, and highly reproducible investigation of islet area and alpha- and beta-cell quantity, as well as position within the islet for either single or large batches of fluorescent images. The algorithm uses active contour models to quantify images accurately and quickly, resulting in an output of an easy-to-read tabular format. Pancreas++ can distinguish between relevant pixels and noise, process multiple islets within the same image, and function without the aid of user interaction.

Input image processing for Pancreas++

Correct formatting of input images for Pancreas++ is vital for accurate quantification results. Variations in the size of the input image, for batch or individual analyses, may result in numerical discrepancies in the user output results. Pancreas++ can process 256x256 .bmp, .jpg, .png, .gif, and .wbmp images. Images that are not of the same size must be scaled; image types not supported by Pancreas++ can be converted to a different file type. It is of crucial importance that alpha cells are green, beta cells are red, and all else neither green nor red.

This software is available for download and is contained in a Winzip file along with the NIH Software Transfer Agreement and a PDF formatted copy of the journal article. Please cite the following paper when employing this tool in publications or other forms of media:
Chen H, Martin B, Cai H, Fiori JL, Egan JM, Siddiqui S and Maudsley S (2013) Pancreas++: automated quantification of pancreatic islet cells in microscopy images. Front. Physio.3:482. doi: 10.3389/fphys.2012.00482