http://www.cnr.it/ontology/cnr/individuo/prodotto/ID195200
Automated segmentation of comet assay images using Gaussian filtering and fuzzy clustering (Articolo in rivista)
- Type
- Label
- Automated segmentation of comet assay images using Gaussian filtering and fuzzy clustering (Articolo in rivista) (literal)
- Anno
- 2012-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1007/s11517-012-0882-z (literal)
- Alternative label
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Sansone M 1; Zeni O 2; Esposito G 1 (literal)
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- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
- Note
- ISI Web of Science (WOS) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- 1. Univ Naples Federico II, I-80100 Naples, Italy; 2. CNR, Inst Electromagnet Sensing Environm IREA, Naples, Italy (literal)
- Titolo
- Automated segmentation of comet assay images using Gaussian filtering and fuzzy clustering (literal)
- Abstract
- Comet assay is one of the most popular tests for the detection of DNA damage at single cell level. In this study, an algorithm for comet assay analysis has been proposed, aiming to minimize user interaction and providing reproducible measurements. The algorithm comprises two-steps: (a) comet identification via Gaussian pre-filtering and morphological operators; (b) comet segmentation via fuzzy clustering. The algorithm has been evaluated using comet images from human leukocytes treated with a commonly used DNA damaging agent. A comparison of the proposed approach with a commercial system has been performed. Results show that fuzzy segmentation can increase overall sensitivity, giving benefits in bio-monitoring studies where weak genotoxic effects are expected. (literal)
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