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Damm D, Wang C, Wei X and Mosig A (2009), "Cell Counting for In Vivo Flow Cytometer Signals Using Wavelet-Based Dynamic Peak Picking", In Biomedical Engineering and Informatics, 2009. BMEI'09. 2nd International Conference on. , pp. 1-4.
BibTeX:
@inproceedings{Damm2009,
  author = {Damm, D. and Wang, C. and Wei, X. and Mosig, A.},
  title = {Cell Counting for In Vivo Flow Cytometer Signals Using Wavelet-Based Dynamic Peak Picking},
  booktitle = {Biomedical Engineering and Informatics, 2009. BMEI'09. 2nd International Conference on},
  year = {2009},
  pages = {1--4}
}
Li Y, Guo J, Wang C, Fan Z, Liu G, Wang C, Gu Z, Damm D, Mosig A and Wei X (2011), "Circulation times of prostate cancer and hepatocellular carcinoma cells by in vivo flow cytometry", Cytometry Part A. Vol. 79(10), pp. 848-854.
BibTeX:
@article{Li2011,
  author = {Li, Y. and Guo, J. and Wang, C. and Fan, Z. and Liu, G. and Wang, C. and Gu, Z. and Damm, D. and Mosig, A. and Wei, X.},
  title = {Circulation times of prostate cancer and hepatocellular carcinoma cells by in vivo flow cytometry},
  journal = {Cytometry Part A},
  year = {2011},
  volume = {79},
  number = {10},
  pages = {848-854}
}
Mosig A, Jager S, Wang C, Nath S, Ersoy I, Palaniappan K-p and Chen S-S (2009), "Tracking cells in Life Cell Imaging videos using topological alignments", Algorithms for Molecular Biology. Vol. 4(1), pp. 10.
Abstract: BACKGROUND:With the increasing availability of live cell imaging technology, tracking cells and other moving objects in live cell videos has become a major challenge for bioimage informatics. An inherent problem for most cell tracking algorithms is over- or under-segmentation of cells - many algorithms tend to recognize one cell as several cells or vice versa.RESULTS:We propose to approach this problem through so-called topological alignments, which we apply to address the problem of linking segmentations of two consecutive frames in the video sequence. Starting from the output of a conventional segmentation procedure, we align pairs of consecutive frames through assigning sets of segments in one frame to sets of segments in the next frame. We achieve this through finding maximum weighted solutions to a generalized "bipartite matching" between two hierarchies of segments, where we derive weights from relative overlap scores of convex hulls of sets of segments. For solving the matching task, we rely on an integer linear program.CONCLUSION:Practical experiments demonstrate that the matching task can be solved efficiently in practice, and that our method is both effective and useful for tracking cells in data sets derived from a so-called Large Scale Digital Cell Analysis System (LSDCAS).AVAILABILITY:The source code of the implementation is available for download from http://www.picb.ac.cn/patterns/Software/topaln webcite.
BibTeX:
@article{Mosig2009Tracking,
  author = {Mosig, Axel and Jager, Stefan and Wang, Chaofeng and Nath, Sumit and Ersoy, Ilker and Palaniappan, Kannap-pan and Chen, Su-Shing},
  title = {Tracking cells in Life Cell Imaging videos using topological alignments},
  journal = {Algorithms for Molecular Biology},
  year = {2009},
  volume = {4},
  number = {1},
  pages = {10},
  url = {http://www.almob.org/content/4/1/10},
  doi = {10.1186/1748-7188-4-10}
}
Wang C, Gui C-P, Liu H-K, Zhang D and Mosig A (2013), "An Image Skeletonization-Based Tool for Pollen Tube Morphology Analysis and PhenotypingF", Journal of Integrative Plant Biology. Vol. 55(2), pp. 131-141. Blackwell Publishing Asia.
Abstract: The mechanism underlying pollen tube growth involves diverse genes and molecular pathways. Alterations in the regulatory genes or pathways cause phenotypic changes reflected by cellular morphology, which can be captured using fluorescence microscopy. Determining and classifying pollen tube morphological phenotypes in such microscopic images is key to our understanding the involvement of genes and pathways. In this context, we propose a computational method to extract quantitative morphological features, and demonstrate that these features reflect morphological differences relevant to distinguish different defects of pollen tube growth. The corresponding software tool furthermore includes a novel semi-automated image segmentation approach, allowing to highly accurately identify the boundary of a pollen tube in a microscopic image.
BibTeX:
@article{Wang2013,
  author = {Wang, Chaofeng and Gui, Cai-Ping and Liu, Hai-Kuan and Zhang, Dong and Mosig, Axel},
  title = {An Image Skeletonization-Based Tool for Pollen Tube Morphology Analysis and PhenotypingF},
  journal = {Journal of Integrative Plant Biology},
  publisher = {Blackwell Publishing Asia},
  year = {2013},
  volume = {55},
  number = {2},
  pages = {131-141},
  url = {http://dx.doi.org/10.1111/j.1744-7909.2012.01184.x},
  doi = {10.1111/j.1744-7909.2012.01184.x}
}
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