In the search of finding a cure for Diabetes, CogneXa teamed up with IKEM to produce a program that can automatically evaluate the quality of pancreatic islets. Pancreatic islets, or Islets of Langerhans, are clusters of cells containing beta cells, which are responsible for the production of the hormone insulin. Beta cells are essential in regulating blood glucose and maintaining normal blood sugar levels. In diabetics, the immune system misidentifies beta cells as dangerous and destroy them, which then causes type 1 diabetes. Given islet cells’ function, doctors are transplanting them in hopes of curing the disease.
Identification of pancreatic islets among other types of tissue and estimation of their total mass is the key for choosing the right donors and acceptors for islet transplantation. Moreover, accurate assessment of the islet mass is vital for medical research in a variety of pancreas-related pursuits, including the quest of finding a cure for diabetes. The process, however, is cumbersome, time-consuming and prone to human error.
We developed a deep-learning neuron network built and trained in our cxflow, that segments and quickly identifies cells viable for transplant. After uploading batches of images to the website www.islenet.com, our program will scan, analyze and evaluate them and promptly generate a report, which doctors can download. For unlimited easy access, permanent links to uploaded batch collections can be generated upon request.
IsletNet is able to segment the images with an over 99.2% f1 score, which provides accurate estimations of islets counts and volumes (>0.99 R^2) in a matter of seconds. Our application is conveniently accessible through our web application www.isletnet.com and is free of charge.
IsleNet accelerates and standardizes the evaluation process of pancreatic islets for surgical transplantation
1.5 months to MVP and 1.5 months to 8 full deployment and production
Segments images with a 99.2% f1 score, speeds up the process (10 seconds vs. 10 minutes), highest accuracy among all available tools (3% error)