Image Processing Methods for the Automated Assessment of Neuronal Outgrowth
Résumé
Neuronal outgrowth assessment is useful to understand the development of peripheral or centralneurons and their regeneration after wounding. It consists in the determination of the length of the cellextensions (neurite length) using photos of neuron cultures. As the manual determination of neurite length istime-consuming and operator-dependent, many semi- or fully-automated methods have been developed. Most ofthem have been designed to analyze fluorescence microscopy images which allow clear delineation of cellbodies and neurites from the background. In this paper, we propose a new easy-to-use fully automated computervision methodbased on denoising, background subtraction, edge and envelope detection, and designed toanalyze compressed images (JPEG format) of non-fluorescent living neurons. A statistical tool was alsointegrated in the program to provide turnkey data to biologists. The reliability of our program was tested usingimages of differentiated PC-12 cell culture. Statistical analysis showed non-significant difference between themanual determination and our automated method