@inproceedings {332,
	title = {Background estimation for microscopic cellular images},
	booktitle = {15th IEEE International Conference on Image Processing, 2008},
	year = {2008},
	abstract = {<p>Background modelling is a key task in tracking applications. Our interest in this paper is the accurate estimation of static backgrounds in scientific imaging, such as those in automated stem cell tracking. In this paper, an effective background estimation method is proposed. First, the segmentation results are used to remove the foreground objects, then the background is robustly estimated over the resultant 3-Dimensional residual image sequence. We do spatio-temporal background estimation over a local neighbourhood with a robust trimmed mean. The experimental results generated by the proposed method are quite promising.</p>
},
	keywords = {automated stem cell tracking, Biomedical Imaging, cellular biophysics, foreground objects removal, image segmentation, image sequence, image sequences, medical image processing, microscopic cellular images, Scientific Imaging, spatio-temporal background estimation, static backgrounds, tracking applications},
	doi = {http://dx.doi.org/10.1109/ICIP.2008.4712436},
	author = {N Nezamoddin Kachouie and P Fieguth}
}
