TY - GEN
T1 - Novel cell segmentation and online learning algorithms for cell phase identification in automated time-lapse microscopy
AU - Wang, Meng
AU - Zhou, Xiaobo
AU - Li, Fuhai
AU - Huckins, Jeremy
AU - King, Randy W.
AU - Wong, Stephen T.
PY - 2007
Y1 - 2007
N2 - Automated identification of cell cycle phases captured via fluorescent microscopy technique is very important for cell cycle understanding and drug discovery. In this paper, we propose a novel cell detection method that utilizes both the intensity and shape information of cell to improve the segmentation quality. In contrast to conventional off-line learning algorithms for classifcation, our study necessitates the on-line adaptivity to accommodate the ever-changing experimental conditions. An Online Support Vector Classifier (OSVC) is thus proposed, which features the removal of support vectors from the old model and assigning the new training examples with different weights according to their importance. Experimental results show the proposed system is effective for cell imaging segmentation and cell phase identification in time-lapse microscopy.
AB - Automated identification of cell cycle phases captured via fluorescent microscopy technique is very important for cell cycle understanding and drug discovery. In this paper, we propose a novel cell detection method that utilizes both the intensity and shape information of cell to improve the segmentation quality. In contrast to conventional off-line learning algorithms for classifcation, our study necessitates the on-line adaptivity to accommodate the ever-changing experimental conditions. An Online Support Vector Classifier (OSVC) is thus proposed, which features the removal of support vectors from the old model and assigning the new training examples with different weights according to their importance. Experimental results show the proposed system is effective for cell imaging segmentation and cell phase identification in time-lapse microscopy.
UR - http://www.scopus.com/inward/record.url?scp=36349029743&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=36349029743&partnerID=8YFLogxK
U2 - 10.1109/ISBI.2007.356789
DO - 10.1109/ISBI.2007.356789
M3 - Conference contribution
AN - SCOPUS:36349029743
SN - 1424406722
SN - 9781424406722
T3 - 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings
SP - 65
EP - 68
BT - 2007 4th IEEE International Symposium on Biomedical Imaging
T2 - 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07
Y2 - 12 April 2007 through 15 April 2007
ER -