Michael Casarona
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Grant: NIH
Michael Casarona
CoPIs:
Lark Bancairen
College:
The Dorothy and George Hennings College of Science, Mathematics, and Technology
Major:
Computational Science & Engineering
Faculty Research Advisor(s):
David Joiner
Abstract:
Our research project “Networked 3D/ VR Cell Virtualization” is focused on creating an open sourced, user-friendly application that allows researchers to create, edit, and analyze custom 3D cell models (generated based on user-defined parameters and 2D confocal images) within a multi-user VR lab. A web front end allows users to create an account that allows them to seamlessly track and edit their models and data. Additionally, users can leverage this online platform to create new models and/ or run an AI cell count analysis, by uploading a series of confocal microscope images; this information is then stored in a database for users to access at a later time or in the VR viewer. The web app also provides a centralized location for users to download the VR viewing software, access documentation, and view user FAQs, making the software easy to obtain and understand. The VR viewing software, created utilizing the Unity Game engine, takes the raw data from the 2D confocal microscope images and layers the sprites on top of each other to create a 3D model, while editing tools allow the user to change the model’s parameters such as the transparency or intensity viewing threshold, to obtain the best view of the cells. The data output from the AI analysis (in the form of x, y, and z coordinates) is used to generate centroid markers for each cell found by the AI tool, which can then be compared to the visual model. Furthermore, Photon Unity Networking 2 (PUN2) allows multiple users to view, interact, and edit the same models in real-time, while Vivox Voice And Text Chat provides built-in text and voice chat functionality, allowing users to discuss the data without the need for third-party software. This application will provide a collaborative platform that enables scientists to count, analyze, and interpret cell data, leveraging a combination of AI analysis and human verification to ensure accuracy and efficiency.