Accurate Morphology Preserving Segmentation of Overlapping Cells based on Active Contours

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http://hdl.handle.net/10138/166928

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Molnar , C , Jermyn , I H , Kato , Z , Rahkama , V , Ostling , P , Mikkonen , P , Pietiainen , V & Horvath , P 2016 , ' Accurate Morphology Preserving Segmentation of Overlapping Cells based on Active Contours ' , Scientific Reports , vol. 6 , 32412 . https://doi.org/10.1038/srep32412

Title: Accurate Morphology Preserving Segmentation of Overlapping Cells based on Active Contours
Author: Molnar, Csaba; Jermyn, Ian H.; Kato, Zoltan; Rahkama, Vesa; Ostling, Paivi; Mikkonen, Piia; Pietiainen, Vilja; Horvath, Peter
Contributor: University of Helsinki, Institute for Molecular Medicine Finland
University of Helsinki, Institute for Molecular Medicine Finland
University of Helsinki, Institute for Molecular Medicine Finland
University of Helsinki, Institute for Molecular Medicine Finland
Date: 2016-08-26
Language: eng
Number of pages: 10
Belongs to series: Scientific Reports
ISSN: 2045-2322
URI: http://hdl.handle.net/10138/166928
Abstract: The identification of fluorescently stained cell nuclei is the basis of cell detection, segmentation, and feature extraction in high content microscopy experiments. The nuclear morphology of single cells is also one of the essential indicators of phenotypic variation. However, the cells used in experiments can lose their contact inhibition, and can therefore pile up on top of each other, making the detection of single cells extremely challenging using current segmentation methods. The model we present here can detect cell nuclei and their morphology even in high-confluency cell cultures with many overlapping cell nuclei. We combine the "gas of near circles" active contour model, which favors circular shapes but allows slight variations around them, with a new data model. This captures a common property of many microscopic imaging techniques: the intensities from superposed nuclei are additive, so that two overlapping nuclei, for example, have a total intensity that is approximately double the intensity of a single nucleus. We demonstrate the power of our method on microscopic images of cells, comparing the results with those obtained from a widely used approach, and with manual image segmentations by experts.
Subject: TREE CROWN EXTRACTION
CANCER
MODELS
MICROSCOPY
CIRCLES
SNAKES
IMAGES
3111 Biomedicine
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