Automated Neuron Tracing and 3D Reconstruction Software

Period of Performance: 02/01/2006 - 01/31/2007

$546K

Phase 2 SBIR

Recipient Firm

Microbrightfield, Inc.
Williston, VT 05495
Principal Investigator

Abstract

DESCRIPTION (provided by applicant): We propose development of a commercial software product, AutoNeuron TM to perform automatic 3D neuron reconstruction. This software will run on a standard desktop PC with the Microsoft Windows(r) operating system and is performed on images acquired from specimen slides. Multiple image modalities can be used, including confocal microscopy, brightfield, and widefield fluorescence. A major innovation of this project is that AutoNeuron will operate in both interactive and unattended modes. Unattended automated tracing of many neuron images will be possible with our robust tracing algorithm based on edge detection and conduit tracking; however, some images will contain complexities that make automated tracing difficult. In these cases, the scientist marks branch points in interactive mode, while the software automatically traces the segment between marked points - accurately locating the centerline and tracing the diameter of the process along its length. In Phase I, we prove the feasibility of applying an advanced tracing algorithm to the larger problem of neuron reconstruction. During this phase we will develop a preliminary user interface with basic editing tools to be used in testing. The software accuracy and efficiency will be assessed comparatively with manual tracings from a variety of neuron types, staining, and imaging methods. Once feasibility of the tracing engine is established, a commercial product will be developed in Phase II. Neuron reconstruction and tracing are important aspects of many analyses of form and function in the nervous system. However, today many valuable studies are not considered because current manual and computer assisted reconstruction techniques are simply too laborious. An automated reconstruction workstation will improve the efficiency and productivity of many currently funded studies as well as future studies once considered impractical.