Pancreatic islet transplantation is emerging as a therapeutic approach for patients affected by diabetes. This approach consists of a minimally invasive procedure replacing insulin-producing cells (pancreatic islets). The technique has been proven successful, but limitations have been identified. One of the major challenges of the procedure is the counting of the isolated pancreatic islets, which is currently jeopardized by subjectivity and inaccuracy. Determination of the accurate islet number is a crucial factor in determining the correlation between the isolation product and clinical outcome. In the proposed study, we have developed software capable of objectively evaluating islet numbers and other viability variables by image analysis. This software is based on image processing and feature extraction algorithms for recognition of the area of interest. This is the first step toward standardization of the isolation outcome and potential clinical success predictability.
- Feature extraction
- Image analysis
- Pancreatic islets transplantation
ASJC Scopus subject areas
- Computer Science Applications
- Artificial Intelligence