Automated cell migration tracking technique: a review

Automated cell migration tracking is important in detecting the cell movement in order to help in cell status analysis especially when there are a huge numbers of cells in one image frame. Automated cell tracking processes involve detecting, segmentation and labelling the cell. Each step is crucial and will affect the next step. The common problems are cell proliferation, overlapping and clustering. Consequently, this review not only focuses on the overview of current techniques used to complete the cell migration tracking tasks, but also the comparison of these techniques and some suggested future work(s).

[1]  Ewert Bengtsson,et al.  Segmentation and Tracking of Neural Stem Cell , 2005, ICIC.

[2]  Hans A. Kestler,et al.  Assessment of Automated Analyses of Cell Migration on Flat and Nanostructured Surfaces , 2012, Computational and structural biotechnology journal.

[3]  Nathalie Harder,et al.  Large‐scale tracking and classification for automatic analysis of cell migration and proliferation, and experimental optimization of high‐throughput screens of neuroblastoma cells , 2015, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

[4]  Takeo Kanade,et al.  Reliably Tracking Partially Overlapping Neural Stem Cells in DIC Microscopy Image Sequences , 2009 .

[5]  N. Jayalakshmi,et al.  Analysis of segmentation and tracking algorithms for time lapse microscopic progenitor cell images , 2010, 2010 International Conference on Signal and Image Processing.

[6]  Shengyong Chen,et al.  A Novel Cell Segmentation, Tracking and Dynamic Analysis Method in Time-Lapse Microscopy Based on Cell Local Graph Structure and Motion Features , 2012, CCPR.

[7]  Philippe Van Ham,et al.  Tracking of migrating cells under phase-contrast video microscopy with combined mean-shift processes , 2005, IEEE Transactions on Medical Imaging.

[8]  Kristian Bredies,et al.  An active-contour based algorithm for the automated segmentation of dense yeast populations on transmission microscopy images , 2011, Comput. Vis. Sci..

[9]  P.K Sahoo,et al.  A survey of thresholding techniques , 1988, Comput. Vis. Graph. Image Process..

[10]  R. Kiss,et al.  Automated tracking of unmarked cells migrating in three-dimensional matrices applied to anti-cancer drug screening. , 2010, Experimental cell research.

[11]  Mohammad Shajib Khadem,et al.  MRI brain image segmentation using graph cuts , 2010 .

[12]  Chunming Tang,et al.  Topological constraint in high-density cells' tracking of image sequences. , 2011, Advances in experimental medicine and biology.

[13]  Erik Meijering,et al.  Methods for cell and particle tracking. , 2012, Methods in enzymology.

[14]  Takeo Kanade,et al.  Cell image analysis: Algorithms, system and applications , 2011, 2011 IEEE Workshop on Applications of Computer Vision (WACV).

[15]  Vartan Kurtcuoglu,et al.  Cell Image Velocimetry (CIV): boosting the automated quantification of cell migration in wound healing assays. , 2012, Integrative biology : quantitative biosciences from nano to macro.

[16]  Mohammad Reza Mahzoun,et al.  Bidirectional Image Thresholding algorithm using combined Edge Detection and P-Tile algorithms , 2011 .

[17]  Hans A. Kestler,et al.  TimeLapseAnalyzer: Multi-target analysis for live-cell imaging and time-lapse microscopy , 2011, Comput. Methods Programs Biomed..

[18]  Bülent Sankur,et al.  Survey over image thresholding techniques and quantitative performance evaluation , 2004, J. Electronic Imaging.

[19]  B. Poornima,et al.  SEGMENTATION AND OBJECT RECOGNITION USING EDGE DETECTION TECHNIQUES , 2010 .

[20]  Ana Maria Mendonça,et al.  Cell Nuclei and Cytoplasm Joint Segmentation Using the Sliding Band Filter , 2010, IEEE Transactions on Medical Imaging.

[21]  K. Rohr,et al.  LARGE-SCALE TRACKING FOR CELL MIGRATION AND PROLIFERATION ANALYSIS AND EXPERIMENTAL OPTIMIZATION OF HIGH-THROUGHPUT SCREENS , 2011 .

[22]  Takeo Kanade,et al.  Automatic cell tracking applied to analysis of cell migration in wound healing assay , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[23]  Justin W. L. Wan,et al.  A combined watershed and level set method for segmentation of brightfield cell images , 2009, Medical Imaging.

[24]  Amjad Rehman,et al.  Medical Image Segmentation Methods, Algorithms, and Applications , 2014 .

[25]  Takeo Kanade,et al.  Reliable cell tracking by global data association , 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[26]  Jerry L. Prince,et al.  A Survey of Current Methods in Medical Image Segmentation , 1999 .