3D Virtual Slide System for Creation and Analysis of Focusable Digital Slides

DESCRIPTION (provided by applicant): The goal of this application is to develop a comprehensive system for the acquisition and quantitative analysis of focusable (3D) virtual slides. A 3D virtual slide is a complete digital representation of a tissue specimen imaged through a microscope, containing the full XY extent of the tissue, captured at the highest possible optical resolution, and including all of the focal planes needed to represent the full Z-extent of the tissue. Digital acquisition of all of the image data contained within a slide specimen enables new methods of automated image analysis, Internet-based sharing of slide material, enhanced collaboration, and digital archiving of slides for improved validation. The essential components of the system that we will develop are: 1) software to drive a computer controlled microscope-based hardware platform to acquire 3D virtual slides, 2) an efficient file format for storage of and access to 3D virtual slides, 3) software for performing quantitative analysis of these large 3D virtual slide images, and 4) software for viewing the 3D virtual slides rapidly over the Internet in a method familiar to a microscopist. Once these four aims are completed, the groundwork will be laid for the development of a new generation of automated analysis tools that can be applied to these virtual slides, resulting in a set of tools for high-throughput quantitative analysis. In the project described here, we will use the Phase I period to develop prototype software designed to acquire, analyze, view, share, and store 3D virtual slides. Phase II of the project will involve development of commercial software for the acquisition of virtual slides and new analysis tools designed to perform automated quantitative analysis of the tissue specimens captured and represented in 3D virtual slides. Relevance: This project will enable brain research to occur at a faster pace than is currently feasible by automating quantitative analyses that are now performed manually. Furthermore, it will lead to the development of new forms of quantitative analysis that are currently impossible. It will facilitate the collaboration between researchers working to find treatments for neurological diseases, and lead to a greater understanding of the brain.