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

Varování

Publikace nespadá pod Lékařskou fakultu, ale pod Fakultu informatiky. Oficiální stránka publikace je na webu muni.cz.

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
Citace
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.
Související projekty:	High-throughput screening of compound libraries aimed on discovery of novel inhibitors of the FGFR/ERK MAP kinase signaling Rozsáhlé výpočetní systémy: modely, aplikace a verifikace IV. Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity