Automated Cell Segmentation in Phase-Contrast Images based on Classification and Region Growing

• Autoři: STOKLASA Roman; BÁLEK Lukáš; KREJČÍ Pavel; MATULA Petr
• Rok publikování: 2015
• Druh: Článek ve sborníku
• Konference: Proceedings of 2015 IEEE International Symposium on Biomedical Imaging, 2015.
• Fakulta / Pracoviště MU: Fakulta informatiky
• www: https://ieeexplore.ieee.org/document/7164149
• Doi: http://dx.doi.org/10.1109/ISBI.2015.7164149
• Obor: Využití počítačů, robotika a její aplikace
• Klíčová slova: phase-contrast microscopy; segmentation; classification; superpixel; cells
• Popis: Cell segmentation in phase-contrast microscopy images remains a challenging problem because of the large variability in subcellular structures and imaging artifacts. In this paper, we present an approach to the automatic segmentation of tightly packed cells in phase-contrast images. We combine the classification of superpixels with the region-growing method to locate cell membrane boundaries. We demonstrate that such a combined approach is able to perform the task of cell detection and segmentation with a high level of precision. On the presented dataset, we achieved 90% precision with 78% recall. The results indicate that this method is suitable for real biological applications.

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