Document Detail


Automated extraction and classification of dynamic metrical features of morphological development in dissociated Purkinje neurons.
MedLine Citation:
PMID:  19837112     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The morphological development of in vitro single cerebellar Purkinje cells obtained from wild type P1 CD1 mice was assessed through a dedicated non-invasive technique based on image processing algorithms and multivariate analysis. Image processing algorithms were implemented to extract metrical features characterizing cell structure and dendritic arborization from sequential optical micrographs. Quantitative morphological features were analyzed in order to identify relevant metrical characteristics common to Purkinje cells in wild type P1 CD1 mice. Cell arborization was found to be characterized by a high fractal dimension and the directionality and level of complexity were shown to be key features for cell morphology classification, as underlined using a three-way PCA analysis.
Authors:
L Billeci; G Pioggia; F Vaglini; A Ahluwalia
Publication Detail:
Type:  Journal Article     Date:  2009-10-28
Journal Detail:
Title:  Journal of neuroscience methods     Volume:  185     ISSN:  1872-678X     ISO Abbreviation:  J. Neurosci. Methods     Publication Date:  2010 Jan 
Date Detail:
Created Date:  2010-02-01     Completed Date:  2010-04-06     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7905558     Medline TA:  J Neurosci Methods     Country:  Netherlands    
Other Details:
Languages:  eng     Pagination:  315-24     Citation Subset:  IM    
Affiliation:
Interdepartmental Research Center E. Piaggio, University of Pisa, via Diotisalvi 2, 56126 Pisa, Italy.
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Animals
Cerebellum / cytology*
Linear Models
Mice
Multivariate Analysis
Nonlinear Dynamics*
Principal Component Analysis
Purkinje Cells / cytology*,  physiology
Radiographic Image Interpretation, Computer-Assisted / methods*
Signal Processing, Computer-Assisted*
Time Factors

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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