Artificial Intelligence in Parkinson’s Disease Research

Two common bottlenecks in research are the time to acquire images and the time for analysis. Reducing this time can lead to an increase in publications for any research group. As a result of pairing the SLIDEVIEW™ VS200 slide scanner with TruAI™ artificial intelligence, data volume has significantly increased for Dr. Ron Tjalkens at Colorado State University. The Tjalkens Group is currently using Olympus’ TruAI deep-learning software to establish neural networks for quantitative determination of the number of neurons and glial cells in multiple brain regions in mouse models of Parkinson’s disease. Images of up to twenty-four whole-brain montages were acquired with the VS200 scanner during a recent demonstration. These images were then uploaded to the TruAI deep learning software, where batch analysis was performed for multiple labels specific to the phenotype of neurons, astrocytes, or microglia. In this presentation you can expect to hear how Dr. Tjalkens use of the VS200 slide scanner and TruAI deep-learning technology are estimated to have reduced a six-month project to just two weeks. TruAI technology has also brought new capabilities by advancing analysis that would be too time consuming and complex by conventional software analysis.