Interactive Visual Analysis of Calcium Imaging Data

With the advances of microscopy techniques, scientists can monitor the neurons in large brain areas of living animals. But at the same time, it creates significant challenges for scientists to make sense of the generated data due to its scale and complexity. This calls for new componential methods and systems for augmenting the current workflows of neuroscientists. This research aims to address this problem by leveraging and innovating advanced machine learning and visualization techniques. We will design, develop, and evaluate an interactive visual solution for the exploration and analysis of calcium imaging data in a human-in-the-loop manner. In this way, our partner’s customers, who are often not machine learning experts, could better harness the complicated models and visually discover insights in data that serve their own domain-specific goals.

Intern: 
Xuejun Du
Faculty Supervisor: 
Jian Zhao
Province: 
Ontario
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