Extraction of Blebs in Human Embryonic Stem Cell Videos

Blebbing is an important biological indicator in determining the health of human embryonic stem cells (hESC). Especially, areas of a bleb sequence in a video are often used to distinguish two cell blebbing behaviors in hESC: dynamic and apoptotic blebbings. This paper analyzes various segmentation methods for bleb extraction in hESC videos and introduces a bio-inspired score function to improve the performance in bleb extraction. Full bleb formation consists of bleb expansion and retraction. Blebs change their size and image properties dynamically in both processes and between frames. Therefore, adaptive parameters are needed for each segmentation method. A score function derived from the change of bleb area and orientation between consecutive frames is proposed which provides adaptive parameters for bleb extraction in videos. In comparison to manual analysis, the proposed method provides an automated fast and accurate approach for bleb sequence extraction.

[1]  J. Tinevez,et al.  Role of cortical tension in bleb growth , 2009, Proceedings of the National Academy of Sciences.

[2]  Erik H. W. Meijering,et al.  Cell Segmentation: 50 Years Down the Road [Life Sciences] , 2012, IEEE Signal Processing Magazine.

[3]  Peter Meer,et al.  Edge Detection with Embedded Confidence , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Fernand Meyer,et al.  Topographic distance and watershed lines , 1994, Signal Process..

[5]  Bir Bhanu,et al.  Use of Video Bioinformatics Tools in Stem Cell Toxicology , 2014 .

[6]  Dorin Comaniciu,et al.  Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  R. E. Wheeler.  Statistical distributions , 1983, APLQ.

[8]  L Mahadevan,et al.  Life and times of a cellular bleb. , 2008, Biophysical journal.

[9]  M. Evans.  Statistical Distributions , 2000 .

[10]  Wanda Strychalski,et al.  A computational model of bleb formation. , 2013, Mathematical medicine and biology : a journal of the IMA.

[11]  Rolf Adams,et al.  Seeded Region Growing , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Peter Meer,et al.  Synergism in low level vision , 2002, Object recognition supported by user interaction for service robots.

[13]  Pierre Soille,et al.  Morphological Image Analysis: Principles and Applications , 2003 .

[14]  Bir Bhanu,et al.  Detection of non-dynamic blebbing single unattached Human Embryonic Stem Cells , 2012, 2012 19th IEEE International Conference on Image Processing.

[15]  P. Talbot,et al.  Comparison of the toxicity of smoke from conventional and harm reduction cigarettes using human embryonic stem cells. , 2010, Toxicological sciences : an official journal of the Society of Toxicology.

[16]  Timothy F. Cootes,et al.  Active Shape Models-Their Training and Application , 1995, Comput. Vis. Image Underst..

[17]  Danwei Huangfu,et al.  Human pluripotent stem cells: an emerging model in developmental biology , 2013, Development.

[18]  P. Talbot,et al.  Mouse and human embryonic stem cells: can they improve human health by preventing disease? , 2011, Current topics in medicinal chemistry.

[19]  R. Leahy,et al.  Magnetic Resonance Image Tissue Classification Using a Partial Volume Model , 2001, NeuroImage.

[20]  Takeo Kanade,et al.  Cell segmentation in microscopy imagery using a bag of local Bayesian classifiers , 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[21]  Fong Yin Lim,et al.  A computational model of amoeboid cell migration , 2013, Computer methods in biomechanics and biomedical engineering.

[22]  Junzhou Huang,et al.  Towards robust and effective shape modeling: Sparse shape composition , 2012, Medical Image Anal..

[23]  Jitendra Malik,et al.  Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[24]  Bir Bhanu,et al.  Reflection Symmetry-Integrated Image Segmentation , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[25]  Barry R. Masters,et al.  Digital Image Processing, Third Edition , 2009 .

[26]  P. Diehl,et al.  Least-Squares Fitting , 1972 .

[27]  Bir Bhanu,et al.  Automated Human Embryonic Stem Cell Detection , 2012, 2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology.