Automated Microtubule Tracking and Analysis

Automated Microtubule Tracking and Analysis by Motaz El-Saban Microtubules are major components of the cytoskeleton and play an important role in a number of cellular functions such as maintaining cell shape, cell division and transport of various molecules. Abnormal dynamic behavior of microtubules has been associated with neuro-degenerative diseases (e.g., Alzheimer) and cancer. Researchers study the dynamics of microtubules under different experimental conditions including different drug treatments, and using time sequence images from fluorescence microscopy. At present the dynamics of microtubules are quantified using simple first and second-order statistical measures of the length variations of manually tracked microtubules. The current analysis being mostly done manually, is quite laborious and time-consuming. Besides, the number of microtubules that one can track with manual methods is limited. In the first part of the thesis, we propose novel tools for automated detection and tracking of microtubules. A multiframe graph-based approach is proposed to tackle tracking issues, and our results demonstrate the robustness of the proposed approach to occlusions and intersections. In the second part of the thesis, we propose the use of statistical modeling tools for a better understanding of the underlying molecular mechanisms of microtubule dynamics. Prototype models are estimated for various experimental conditions by training

[1]  Qiang Ji,et al.  Enhancement of microtubules in EM tomography , 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).

[2]  Chong-Wah Ngo,et al.  On clustering and retrieval of video shots , 2001, MULTIMEDIA '01.

[3]  B. S. Manjunath,et al.  Panoramic capturing and recognition of human activity , 2002, Proceedings. International Conference on Image Processing.

[4]  Rachid Deriche,et al.  Geodesic Active Contours and Level Sets for the Detection and Tracking of Moving Objects , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  V. Caselles,et al.  Snakes in Movement , 1996 .

[6]  Josiane Zerubia,et al.  Higher order active contours and their application to the detection of line networks in satellite imagery. , 2003, ICCV 2003.

[7]  Mubarak Shah,et al.  A noniterative greedy algorithm for multiframe point correspondence , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Jiawei Han,et al.  MultiMediaMiner: a system prototype for multimedia data mining , 1998, SIGMOD '98.

[9]  M. Jordan,et al.  Suppression of microtubule dynamics by epothilone B is associated with mitotic arrest. , 2003, Cancer research.

[10]  David Tuck,et al.  Automatic quantification of microtubule dynamics , 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).

[11]  Dimitris N. Metaxas,et al.  ASL recognition based on a coupling between HMMs and 3D motion analysis , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[12]  Ilya Zaliapin,et al.  Multiscale trend analysis of microtubule transport in melanophores. , 2005, Biophysical journal.

[13]  Holy,et al.  Microtubule dynamics: Caps, catastrophes, and coupled hydrolysis. , 1996, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[14]  Scott T. Acton,et al.  Vessel boundary tracking for intravital microscopy via multiscale gradient vector flow snakes , 2004, IEEE Transactions on Biomedical Engineering.

[15]  J. McIntosh,et al.  A molecular-mechanical model of the microtubule. , 2005, Biophysical journal.

[16]  G. Aubert,et al.  Tracking video objects using active contours , 2002, Workshop on Motion and Video Computing, 2002. Proceedings..

[17]  Qiang Ji,et al.  Automated Extraction of Microtubules and Their Plus-Ends , 2005, 2005 Seventh IEEE Workshops on Applications of Computer Vision (WACV/MOTION'05) - Volume 1.

[18]  James S. Duncan,et al.  Segmentation and 3D Reconstruction of Microtubules in Total Internal Reflection Fluorescence Microscopy (TIRFM) , 2005, MICCAI.

[19]  Slobodan Ribaric,et al.  A system for tracking laboratory animals based on optical flow and active contours , 2001, Proceedings 11th International Conference on Image Analysis and Processing.

[20]  Chris Chatfield,et al.  The Analysis of Time Series : An Introduction, Sixth Edition , 2003 .

[21]  Sitaram Bhagavathy,et al.  SketchIt: Basketball Video Retrieval Using Ball Motion Similarity , 2004, PCM.

[22]  Scott T. Acton,et al.  Level set analysis for leukocyte detection and tracking , 2004, IEEE Transactions on Image Processing.

[23]  Shih-Fu Chang,et al.  Feature selection for unsupervised discovery of statistical temporal structures in video , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[24]  Jianping Fan,et al.  Medical video mining for efficient database indexing, management and access , 2003, Proceedings 19th International Conference on Data Engineering (Cat. No.03CH37405).

[25]  Robert A. Lordo,et al.  Learning from Data: Concepts, Theory, and Methods , 2001, Technometrics.

[26]  Dennis McLeod,et al.  Mining gene expression datasets using density-based clustering , 2004, CIKM '04.

[27]  James S. Duncan,et al.  Tracking the motion of the outer tips of microtubules , 2006, 3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006..

[28]  B. S. Manjunath,et al.  Interactive segmentation using curve evolution and relevance feedback , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[29]  G. Danuser,et al.  Quantitative fluorescent speckle microscopy: where it came from and where it is going , 2003, Journal of microscopy.

[30]  Wei Xiong,et al.  Query by video clip , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[31]  Hisashi Miyamori,et al.  Video annotation for content-based retrieval using human behavior analysis and domain knowledge , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[32]  Leslie Wilson,et al.  βIII-Tubulin Induces Paclitaxel Resistance in Association with Reduced Effects on Microtubule Dynamic Instability* , 2005, Journal of Biological Chemistry.

[33]  Ramesh C. Jain,et al.  Using Dynamic Programming for Solving Variational Problems in Vision , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[34]  Anil K. Jain,et al.  Automatic classification of tennis video for high-level content-based retrieval , 1998, Proceedings 1998 IEEE International Workshop on Content-Based Access of Image and Video Database.

[35]  Kuniaki Uehara,et al.  Mining video editing rules in video streams , 2002, MULTIMEDIA '02.

[36]  B. S. Manjunath,et al.  Automated tracking and modeling of microtubule dynamics , 2006, 3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006..

[37]  Rama Chellappa,et al.  Identification of humans using gait , 2004, IEEE Transactions on Image Processing.

[38]  Sebastian Stier,et al.  Extraction of line properties based on direction fields , 1996, IEEE Trans. Medical Imaging.

[39]  Josef Kittler,et al.  Hierarchical decision making scheme for sports video categorisation with temporal post-processing , 2004, CVPR 2004.

[40]  B. S. Manjunath,et al.  Activity Analysis in Microtubule Videos by Mixture of Hidden Markov Models , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[41]  Daniel Kifer,et al.  DualMiner: A Dual-Pruning Algorithm for Itemsets with Constraints , 2002, Data Mining and Knowledge Discovery.

[42]  HongJiang Zhang,et al.  Automatic parsing of TV soccer programs , 1995, Proceedings of the International Conference on Multimedia Computing and Systems.

[43]  S. Feinstein,et al.  Modulation of microtubule dynamics by tau in living cells: implications for development and neurodegeneration. , 2004, Molecular biology of the cell.

[44]  Alfred M. Bruckstein,et al.  Regularized Laplacian Zero Crossings as Optimal Edge Integrators , 2003, International Journal of Computer Vision.

[45]  M. Jordan,et al.  Microtubules as a target for anticancer drugs , 2004, Nature Reviews Cancer.

[46]  Milind R. Naphade,et al.  A probabilistic framework for semantic video indexing, filtering, and retrieval , 2001, IEEE Trans. Multim..

[47]  A. Murat Tekalp,et al.  Probabilistic Analysis and Extraction of Video Content , 1999, ICIP.

[48]  Jake K. Aggarwal,et al.  Line Correspondences from Cooperating Spatial and Temporal Grouping Processes for a Sequence of Images , 1997, Comput. Vis. Image Underst..

[49]  J. Pearson,et al.  Geometric features of microtubule dynamics , 1998 .

[50]  Chris Chatfield,et al.  The Analysis of Time Series: An Introduction , 1981 .

[51]  Tiecheng Liu,et al.  A hidden Markov model approach to the structure of documentaries , 2000, 2000 Proceedings Workshop on Content-based Access of Image and Video Libraries.

[52]  Ramakrishnan Srikant,et al.  Fast algorithms for mining association rules , 1998, VLDB 1998.

[53]  Jean-Francois Mangin,et al.  Detection of linear features in SAR images: application to road network extraction , 1998, IEEE Trans. Geosci. Remote. Sens..

[54]  G Danuser,et al.  Yeast kinetochore microtubule dynamics analyzed by high-resolution three-dimensional microscopy. , 2005, Biophysical journal.

[55]  B. S. Manjunath,et al.  Scalable spatial event representation , 2002, Proceedings. IEEE International Conference on Multimedia and Expo.

[56]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[57]  C.-C. Jay Kuo,et al.  Rule-based video classification system for basketball video indexing , 2000, MULTIMEDIA '00.

[58]  Badrinath Roysam,et al.  Automated semantic analysis of changes in image sequences of neurons in culture , 2006, IEEE Transactions on Biomedical Engineering.

[59]  Christos Faloutsos,et al.  VideoTrails: representing and visualizing structure in video sequences , 1997, MULTIMEDIA '97.

[60]  T. Mitchison,et al.  Microtubule polymerization dynamics. , 1997, Annual review of cell and developmental biology.

[61]  Qiang Ji,et al.  Model-based automated segmentation of kinetochore microtubule from electron tomography , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[62]  Ramakant Nevatia,et al.  Representation and optimal recognition of human activities , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[63]  P Wadsworth,et al.  Taxol suppresses dynamics of individual microtubules in living human tumor cells. , 1999, Molecular biology of the cell.

[64]  B. S. Manjunath,et al.  A Texture Thesaurus for Browsing Large Aerial Photographs , 1998, J. Am. Soc. Inf. Sci..

[65]  Tony Lindeberg,et al.  Edge Detection and Ridge Detection with Automatic Scale Selection , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[66]  Alice Caplier,et al.  Accurate and quasi-automatic lip tracking , 2004, IEEE Transactions on Circuits and Systems for Video Technology.

[67]  Johan Montagnat,et al.  Shape and Topology Constraints on Parametric Active Contours , 2001, Comput. Vis. Image Underst..

[68]  I. Borg.  Multidimensional similarity structure analysis , 1987 .

[69]  B. S. Manjunath,et al.  Towards automated bioimage analysis: from features to semantics , 2006, 3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006..

[70]  Hai Tao,et al.  Object Tracking with Bayesian Estimation of Dynamic Layer Representations , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[71]  Shih-Fu Chang,et al.  A fully automated content-based video search engine supporting spatiotemporal queries , 1998, IEEE Trans. Circuits Syst. Video Technol..

[72]  James A. Sethian,et al.  Level Set Methods and Fast Marching Methods , 1999 .

[73]  David A. Forsyth,et al.  Finding and tracking people from the bottom up , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[74]  Leslie Wilson,et al.  Inability of tau to properly regulate neuronal microtubule dynamics: a loss-of-function mechanism by which tau might mediate neuronal cell death. , 2005, Biochimica et biophysica acta.

[75]  Alex Pentland,et al.  Invariant features for 3-D gesture recognition , 1996, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition.

[76]  Ron Kimmel,et al.  Numerical geometry of images - theory, algorithms, and applications , 2003 .

[77]  M. Eisen,et al.  Exploring the conditional coregulation of yeast gene expression through fuzzy k-means clustering , 2002, Genome Biology.

[78]  J. Bulinski,et al.  Abundant expression of the microtubule-associated protein, ensconsin (E-MAP-115), alters the cellular response to Taxol. , 2001, Cell motility and the cytoskeleton.

[79]  H. Flyvbjerg,et al.  Microtubule dynamics. II. Kinetics of self-assembly , 1997 .

[80]  Mubarak Shah,et al.  Object based segmentation of video using color, motion and spatial information , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[81]  Eric N. Cytrynbaum,et al.  Centering of a radial microtubule array by translocation along microtubules spontaneously nucleated in the cytoplasm , 2005, Nature Cell Biology.

[82]  J. Todd.  Book Review: Digital image processing (second edition). By R. C. Gonzalez and P. Wintz, Addison-Wesley, 1987. 503 pp. Price: £29.95. (ISBN 0-201-11026-1) , 1988 .

[83]  J. Sethian,et al.  A Fast Level Set Method for Propagating Interfaces , 1995 .

[84]  D. Dohrman,et al.  Chronic ethanol exposure increases microtubule content in PC12 cells , 2005, BMC Neuroscience.

[85]  Qiang Ji,et al.  Extraction of 3D microtubules axes from cellular electron tomography images , 2002, Object recognition supported by user interaction for service robots.

[86]  R. Pepperkok,et al.  Chromosome-induced microtubule assembly mediated by TPX2 is required for spindle formation in HeLa cells , 2002, Nature Cell Biology.

[87]  B. S. Manjunath,et al.  Video region segmentation by spatio-temporal watersheds , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[88]  G Danuser,et al.  Tracking differential interference contrast diffraction line images with nanometre sensitivity , 2000, Journal of microscopy.

[89]  Vannary Meas-Yedid,et al.  Segmentation and tracking of migrating cells in videomicroscopy with parametric active contours: a tool for cell-based drug testing , 2002, IEEE Transactions on Medical Imaging.

[90]  Sergio A. Velastin,et al.  A method for obtaining neural network training sets in video sequences , 2000, Proceedings Third IEEE International Workshop on Visual Surveillance.

[91]  G. Borisy,et al.  Centrosomal control of microtubule dynamics. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[92]  Jianping Fan,et al.  ClassMiner: mining medical video for scalable skimming and summarization , 2002, MULTIMEDIA '02.

[93]  Trevor Darrell,et al.  Constraining human body tracking , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[94]  Roberto Cipolla,et al.  Real-Time Visual Tracking of Complex Structures , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[95]  B. S. Manjunath,et al.  NeTra-V: toward an object-based video representation , 1997, Electronic Imaging.

[96]  Jerry L. Prince,et al.  Gradient vector flow: a new external force for snakes , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[97]  Robert Marti,et al.  Tracking Mammographic Structures Over Time , 2001, BMVC.

[98]  Joost van de Weijer,et al.  Fast Anisotropic Gauss Filtering , 2002, ECCV.

[99]  Shih-Fu Chang,et al.  Structure analysis of sports video using domain models , 2001, IEEE International Conference on Multimedia and Expo, 2001. ICME 2001..

[100]  Carsten Steger,et al.  An Unbiased Detector of Curvilinear Structures , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[101]  Junji Maeda,et al.  Representation and retrieval of video scene by using object actions and their spatio-temporal relationships , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[102]  Ioannis Patras,et al.  Video Segmentation by MAP Labeling of Watershed Segments , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[103]  Rama Chellappa,et al.  "Shape Activity": a continuous-state HMM for moving/deforming shapes with application to abnormal activity detection , 2005, IEEE Transactions on Image Processing.

[104]  Biing-Hwang Juang,et al.  Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.

[105]  Laurent D. Cohen,et al.  On active contour models and balloons , 1991, CVGIP Image Underst..

[106]  Stefan Eickeler,et al.  Content-based video indexing of TV broadcast news using hidden Markov models , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[107]  Murat Kunt,et al.  Spatiotemporal Segmentation Based on Region Merging , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[108]  Enrico Gratton,et al.  Organelle transport along microtubules in Xenopus melanophores: evidence for cooperation between multiple motors. , 2006, Biophysical journal.

[109]  Jenq-Neng Hwang,et al.  Detecting objects in image sequences using rule-based control in an active contour model , 2003, IEEE Transactions on Biomedical Engineering.

[110]  Timothy J. Mitchison,et al.  Direct observation of microtubule dynamics at kinetochores in Xenopus extract spindles , 2003, The Journal of cell biology.

[111]  Ronald Fedkiw,et al.  Level set methods and dynamic implicit surfaces , 2002, Applied mathematical sciences.

[112]  Behrooz Kamgar-Parsi,et al.  Algorithms for matching 3D line sets , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[113]  Wen-Liang Hwang,et al.  Wavelet based active contour model for object tracking , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[114]  Guillermo Sapiro,et al.  Geodesic Active Contours , 1995, International Journal of Computer Vision.

[115]  J. Sethian,et al.  Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations , 1988 .

[116]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[117]  Sanjeev R. Kulkarni,et al.  Automated analysis and annotation of basketball video , 1997, Electronic Imaging.

[118]  H. Lodish.  Molecular Cell Biology , 1986 .