| Literature DB >> 20949295 |
Dan Dominik Brüllmann1, Andreas Pabst, Karl M Lehmann, Thomas Ziebart, Marc O Klein, Bernd d'Hoedt.
Abstract
In this article, we describe a new image analysis software that allows rapid segmentation and separation of fluorescently stained cell nuclei using a fast ellipse detection algorithm. Detection time ranged between 1.84 and 3.14 s. Segmentation results were compared with manual evaluation. The achieved over-segmentation rate was 0.11 (0.1 double counts and 0.01 false positive detections), and the under-segmentation rate was of 0.03 over all images. We demonstrate the applicability of the proposed algorithm to automated counting of fluorescent-labeled cell nuclei and to tissue characterization. Moreover, the performance of the proposed algorithm is compared with preexisting automated image analysis techniques described by others.Entities:
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Year: 2010 PMID: 20949295 DOI: 10.1007/s00784-010-0479-6
Source DB: PubMed Journal: Clin Oral Investig ISSN: 1432-6981 Impact factor: 3.573