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© 2016. This article is published under (http://creativecommons.org/licenses/by-nc-sa/3.0/) (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Glaucoma is a multifactorial optic neuropathy characterized by the damage and death of the retinal ganglion cells. This disease results in vision loss and blindness. Any vision loss resulting from the disease cannot be restored and nowadays there is no available cure for glaucoma; however an early detection and treatment, could offer neuronal protection and avoid later serious damages to the visual function. A full understanding of the etiology of the disease will still require the contribution of many scientific efforts. Glial activation has been observed in glaucoma, being microglial proliferation a hallmark in this neurodegenerative disease. A typical project studying these cellular changes involved in glaucoma often needs thousands of images - from several animals - covering different layers and regions of the retina. The gold standard to evaluate them is the manual count. This method requires a large amount of time from specialized personnel. It is a tedious process and prone to human error. We present here a new method to count microglial cells by using a computer algorithm. It counts in one hour the same number of images that a researcher counts in four weeks, with no loss of reliability.

Details

Title
Automatic counting of microglial cell activation and its applications
Author
Gallego, Beatriz 1 ; de Gracia, Pablo 2 

 Instituto de Investigaciones Oftalmológicas Ramón Castroviejo; Facultad de Óptica y Optometría, Departamento de Oftalmología y Otorrinolaringología, Universidad Complutense de Madrid, Madrid 
 Midwestern University, Chicago College of Optometry, Downers Grove, IL; Department of Neurobiology, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ 
Pages
1212-1215
Publication year
2016
Publication date
Aug 2016
Publisher
Medknow Publications & Media Pvt. Ltd.
ISSN
16735374
e-ISSN
18767958
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2382724764
Copyright
© 2016. This article is published under (http://creativecommons.org/licenses/by-nc-sa/3.0/) (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.