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Clin Oral Investig. 2012 Feb;16(1):33-8. doi: 10.1007/s00784-010-0479-6. Epub 2010 Oct 15.

Counting touching cell nuclei using fast ellipse detection to assess in vitro cell characteristics: a feasibility study.

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Department of Oral Surgery, University Medical Center of Johannes Gutenberg University Mainz, Augustusplatz 2, 55131, Mainz, Germany.


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.

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