Open AccessA neurite quality index and machine vision software for improved quantification of neurodegeneration
Author(s) -
Peggy L. Romero,
T. M. Miller,
Arman Garakani
Publication year - 2009
Publication title -
biotechniques/biotechniques
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.617
H-Index - 131
eISSN - 1940-9818
pISSN - 0736-6205
DOI - 10.2144/000113305
Subject(s) - neurite , neurodegeneration , neuroprotection , dorsal root ganglion , computer science , artificial intelligence , dorsum , neuroscience , biology , machine learning , medicine , pathology , anatomy , biochemistry , disease , in vitro
Current methods to assess neurodegradation in dorsal root ganglion cultures as a model for neurodegenerative diseases are imprecise and time-consuming. Here we describe two new methods to quantify neuroprotection in these cultures. The neurite quality index (NQI) builds upon earlier manual methods, incorporating additional morphological events to increase detection sensitivity for the detection of early degeneration events. Neurosight is a machine vision-based method that recapitulates many of the strengths of NQI while enabling high-throughput screening applications with decreased costs.