Free Content Automatic quantification of viability in epithelial cell cultures by texture analysis

Authors: Malpica, N.1; Santos, A.1; Tejedor, A.2; Torres, A.2; Castilla, M.2; García-Barreno, P.2; Desco, M.2

Source: Journal of Microscopy, Volume 209, Number 1, January 2003 , pp. 34-40(7)

Publisher: Wiley-Blackwell

Buy & download fulltext article:

You have access to the full text article on a website external to ingentaconnect.

Please click here to view this article on Wiley Online Library.

You may be required to register and activate access on Wiley Online Library before you can obtain the full text. If you have any queries please visit Wiley Online Library

Abstract:

Summary

Quantification of live cells in phase contrast microscopy images allows in vivo assessment of the viability of cultured cells. An automatic screening procedure seems advisable because of the large number of cells that must be counted to achieve reasonable accuracy. This paper presents a method that quantifies necrosis in cell cultures by texture analysis of microscope images.

The image is divided into regions of equal size that are classified by means of a segmentation algorithm based on texture analysis into three categories: live cells, necrotic cells and background. The classification uses three discriminant functions, built from parameters derived from the histogram and the co-occurrence matrix and calculated by performing an initial stepwise discriminant analysis on 21 sample images from a training set.

The areas occupied by live and necrotic cells and number of live cells have been obtained for primary cellular cultures in intervals of 48 h during 2 weeks. The results have been compared with those obtained by an experienced observer, showing a very good correlation (Pearson's coefficient 0.95, kappa 0.87, N= 1600).

A method has been developed that provides an accuracy similar to that provided by an expert, while allowing a much higher number of fields to be counted.

Keywords: Automated microscopy; cell culture; co-occurrence matrix; cytometry; image analysis; segmentation; texture

Document Type: Research article

DOI: http://dx.doi.org/10.1046/j.1365-2818.2003.01094.x

Affiliations: 1: Departamento de Ingeniería Electrónica, ETSI Telecomunicación Universidad Politécnica de Madrid Ciudad Universitaria s/n, E-28040, Madrid, Spain 2: Medicina Experimental, Hospital General Universitario `Gregorio Marañón' C/Dr Esquerdo, 46 E-28007 Madrid, Spain

Publication date: 2003-01-01

Related content

Tools

Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content

Text size:

A | A | A | A
Share this item with others: These icons link to social bookmarking sites where readers can share and discover new web pages. print icon Print this page