@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},
	}