LIA can be utilized to perform analysis of microscopic images to automatically evaluate the quality of pancreatic islets. This approach reliably identifies pancreatic islets among other types of tissue and carries out an estimation of their total mass. This is a crucial piece of information when choosing the right donors and acceptors for islet transplantation.
In partnership with an established healthcare institution in Prague, Cognexa has developed a deep-learning network built and trained in cxflow
that automatically segments and evaluates the quality of pancreatic (Langerhans) islets and which can now be accessed via www.islenet.com
. The software automatically scans, analyzes and evaluates all images and promptly generates reports for the endocrinologist, thus saving hundreds of hours of manual lab work.