Abstract | ||
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Automatic discrimination and quantification of alive and dead cells in phase contrast microscopy images allows in vivo analysis of the viability of cultured cells without staining. Unsupervised segmentation, based on texture analysis, classifies each image region into three groups: live cells, necrotic cells and background. The segmentation is based on three discriminant functions, built using a total of 12 parameters derived from the histogram and the co-occurrence matrix. These parameters were selected performing a discriminant. analysis on a training set that included images from three different cultures. Once images are automatically segmented, the approximate number of live and dead cells is obtained by dividing each area by the average size of each cell type. The number and percentage of live and necrotic cells have been obtained for primary cellular cultures in intervals of 48 hr. during two weeks. The results have been compared with the figures given by an experienced human observer, showing a very good correlation (Pearson's coefficient 0.95, kappa 0.87). A reliable and easy to-use tool has been developed. It provides quantitative results on phase contrast microscopy images of cell cultures, with preliminary results showing accuracy similar to that provided by an expert, allowing to count a higher number of fields. |
Year | DOI | Venue |
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2001 | 10.1117/12.431074 | Proceedings of SPIE |
Keywords | Field | DocType |
cell culture,texture,segmentation,cytometry,automated microscopy,co-occurence matrix | Cell culture,Computer vision,Histogram,Kappa,Pattern recognition,Biology,Segmentation,Cell type,Artificial intelligence,Microscopy,Linear discriminant analysis,Cytometry | Conference |
Volume | ISSN | Citations |
4322 | 0277-786X | 2 |
PageRank | References | Authors |
0.53 | 2 | 9 |
Name | Order | Citations | PageRank |
---|---|---|---|
A Santos | 1 | 281 | 26.52 |
cristina ramiro | 2 | 2 | 0.53 |
Manuel Desco | 3 | 174 | 19.81 |
N. Malpica | 4 | 45 | 7.25 |
alberto tejedor | 5 | 2 | 0.53 |
ana m herrera torres | 6 | 2 | 0.53 |
María J. Ledesma-carbayo | 7 | 329 | 33.77 |
manuela castilla | 8 | 2 | 0.53 |
P García-Barreno | 9 | 10 | 1.83 |