%0 Journal Article
	%A Andreas Heindl and  Alexander K. Seewald and  Martin Schepelmann and  Radu Rogojanu and  Giovanna Bises and 
Theresia Thalhammer and  Isabella Ellinger
	%D 2012
	%J International Journal of Medical and Health Sciences
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 67, 2012
	%T A Novel Nucleus-Based Classifier for Discrimination of Osteoclasts and Mesenchymal Precursor Cells in Mouse Bone Marrow Cultures
	%U https://publications.waset.org/pdf/81
	%V 67
	%X Bone remodeling occurs by the balanced action of
bone resorbing osteoclasts (OC) and bone-building osteoblasts.
Increased bone resorption by excessive OC activity contributes
to malignant and non-malignant diseases including osteoporosis.
To study OC differentiation and function, OC formed in
in vitro cultures are currently counted manually, a tedious
procedure which is prone to inter-observer differences. Aiming
for an automated OC-quantification system, classification of
OC and precursor cells was done on fluorescence microscope
images based on the distinct appearance of fluorescent nuclei.
Following ellipse fitting to nuclei, a combination of eight
features enabled clustering of OC and precursor cell nuclei.
After evaluating different machine-learning techniques, LOGREG
achieved 74% correctly classified OC and precursor cell
nuclei, outperforming human experts (best expert: 55%). In
combination with the automated detection of total cell areas,
this system allows to measure various cell parameters and most
importantly to quantify proteins involved in osteoclastogenesis.
	%P 304 - 309