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Computer‐assisted motion analysis of neuronal cell growth
Author(s) -
Hawkins Stacy S.,
Buettner Helen M.,
Dunn Stanley M.
Publication year - 1997
Publication title -
journal of applied polymer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.575
H-Index - 166
eISSN - 1097-4628
pISSN - 0021-8995
DOI - 10.1002/(sici)1097-4628(19970314)63:11<1413::aid-app3>3.0.co;2-p
Subject(s) - neurite , growth cone , neuroscience , dynamics (music) , regeneration (biology) , biological system , cell growth , computer science , focus (optics) , characterization (materials science) , motion (physics) , artificial intelligence , chemistry , biophysics , biology , nanotechnology , microbiology and biotechnology , materials science , physics , axon , optics , biochemistry , acoustics , in vitro
Characterization of neuronal cell growth provides key information about the development of neural pathways during embryogenesis as well as their regeneration following postnatal nerve injury. However, very active cell types like growing neurons are difficult to track in detail because their motion is complex and cellular features have a tendency to move out of the focal plane or occlude one another. Due to these difficulties, characterization of neuronal growth dynamics has been less quantitative than desired. To address this problem, we developed a method for the automated motion analysis of neuronal growth based on image analysis and shape correspondence techniques. This method increases the rate at which we can obtain dynamic data by at least an order of magnitude. We focus specifically on the growth cone , a specialized, cell‐like structure at the growing neurite tip whose behavior is believed to be a key determinant of neuronal growth. © 1997 John Wiley & Sons, Inc. J Appl Polym Sci 63: 1413–1422, 1997