@article{(Open Science Index):https://publications.waset.org/pdf/81, title = {A Novel Nucleus-Based Classifier for Discrimination of Osteoclasts and Mesenchymal Precursor Cells in Mouse Bone Marrow Cultures}, author = {Andreas Heindl and Alexander K. Seewald and Martin Schepelmann and Radu Rogojanu and Giovanna Bises and Theresia Thalhammer and Isabella Ellinger}, country = {}, institution = {}, abstract = {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.}, journal = {International Journal of Medical and Health Sciences}, volume = {6}, number = {7}, year = {2012}, pages = {304 - 309}, ee = {https://publications.waset.org/pdf/81}, url = {https://publications.waset.org/vol/67}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 67, 2012}, }