[Cite as http://purl.org/au-research/grants/arc/DE160100241]
Researchers Dr Luping Zhou
Brief description This project aims to develop a probabilistic inference framework based on graphical models to enable discriminative, interpretable and reliable analysis of brain imaging data. Recent development of computer-assisted neuroimage analysis calls for advanced pattern recognition methods. To meet this requirement, this project proposes a framework that addresses several critical issues in this process, and to provide important models and algorithms to identify brain connectivity patterns and benefit the diagnosis of diseases. The output of this project is expected to include a set of effective computational algorithms and computer-assisted tools, which can help medical researchers to identify brain disorders with better precision, repeatability and objectivity.
Funding Amount $300,000
Funding Scheme Discovery Early Career Researcher Award