publication . Preprint . 2017

Cell Tracking via Proposal Generation and Selection

Akram, Saad Ullah; Kannala, Juho; Eklund, Lauri; Heikkilä, Janne;
Open Access English
  • Published: 09 May 2017
Abstract
Microscopy imaging plays a vital role in understanding many biological processes in development and disease. The recent advances in automation of microscopes and development of methods and markers for live cell imaging has led to rapid growth in the amount of image data being captured. To efficiently and reliably extract useful insights from these captured sequences, automated cell tracking is essential. This is a challenging problem due to large variation in the appearance and shapes of cells depending on many factors including imaging methodology, biological characteristics of cells, cell matrix composition, labeling methodology, etc. Often cell tracking metho...
Subjects
free text keywords: Computer Science - Computer Vision and Pattern Recognition
Related Organizations
Download from
44 references, page 1 of 3

[1] X. Trepat, Z. Chen, and K. Jacobson. “Cell migration.” In: Comprehensive Physiology (2012) (cit. on p. 1).

[2] C. Zimmer et al. “Segmentation and tracking of migrating cells in videomicroscopy with parametric active contours: a tool for cell-based drug testing”. In: T-MI (2002) (cit. on pp. 1, 2).

[3] F. Amat et al. “Fast, accurate reconstruction of cell lineages from large-scale fluorescence microscopy data.” In: Nature methods (2014) (cit. on pp. 1, 2).

[4] C. Zimmer et al. “On the digital trail of mobile cells”. In: IEEE Signal Processing Magazine (2006) (cit. on p. 1).

[5] O. Hilsenbeck et al. “Software tools for single-cell tracking and quantification of cellular and molecular properties”. In: Nature Biotechnology (2016) (cit. on pp. 1, 2). [OpenAIRE]

[6] B. Neumann et al. “Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes.” In: Nature (2010) (cit. on p. 1).

[7] K. W. Eliceiri et al. “Biological imaging software tools”. In: Nature Methods (2012) (cit. on pp. 1, 2).

[8] Z. Liu and P. J. Keller. “Emerging Imaging and Genomic Tools for Developmental Systems Biology”. In: Developmental Cell (2016) (cit. on p. 1).

[9] E. Meijering et al. “Tracking in cell and developmental biology.” In: Seminars in cell & developmental biology (2009) (cit. on p. 1). [OpenAIRE]

[10] P. Matula et al. “Cell Tracking Accuracy Measurement Based on Comparison of Acyclic Oriented Graphs”. In: PLoS ONE (2015) (cit. on pp. 1, 5, 10). [OpenAIRE]

[11] E. Meijering, O. Dzyubachyk, and I. Smal. “Methods for cell and particle tracking.” In: Methods in enzymology (2012) (cit. on pp. 1, 2). [OpenAIRE]

[12] M. Masˇka et al. “A Benchmark for Comparison of Cell Tracking Algorithms”. In: Bioinformatics (2014) (cit. on pp. 1, 2, 7, 8).

[13] C Held and V. Wiesmann. “Review of free software tools for image analysis of fluorescence cell micrographs”. In: Journal of Microscopy (2015) (cit. on pp. 1, 2).

[14] E. Tu¨retken et al. “Globally Optimal Cell Tracking using Integer Programming”. In: arXiv:1501.05499 (2015) (cit. on pp. 2, 3, 5-8, 10-12).

[15] S. U. Akram et al. “Cell Segmentation Proposal Network for Microscopy Image Analysis”. In: DLMIA (MICCAI-W). 2016 (cit. on pp. 2, 3, 5).

44 references, page 1 of 3
Abstract
Microscopy imaging plays a vital role in understanding many biological processes in development and disease. The recent advances in automation of microscopes and development of methods and markers for live cell imaging has led to rapid growth in the amount of image data being captured. To efficiently and reliably extract useful insights from these captured sequences, automated cell tracking is essential. This is a challenging problem due to large variation in the appearance and shapes of cells depending on many factors including imaging methodology, biological characteristics of cells, cell matrix composition, labeling methodology, etc. Often cell tracking metho...
Subjects
free text keywords: Computer Science - Computer Vision and Pattern Recognition
Related Organizations
Download from
44 references, page 1 of 3

[1] X. Trepat, Z. Chen, and K. Jacobson. “Cell migration.” In: Comprehensive Physiology (2012) (cit. on p. 1).

[2] C. Zimmer et al. “Segmentation and tracking of migrating cells in videomicroscopy with parametric active contours: a tool for cell-based drug testing”. In: T-MI (2002) (cit. on pp. 1, 2).

[3] F. Amat et al. “Fast, accurate reconstruction of cell lineages from large-scale fluorescence microscopy data.” In: Nature methods (2014) (cit. on pp. 1, 2).

[4] C. Zimmer et al. “On the digital trail of mobile cells”. In: IEEE Signal Processing Magazine (2006) (cit. on p. 1).

[5] O. Hilsenbeck et al. “Software tools for single-cell tracking and quantification of cellular and molecular properties”. In: Nature Biotechnology (2016) (cit. on pp. 1, 2). [OpenAIRE]

[6] B. Neumann et al. “Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes.” In: Nature (2010) (cit. on p. 1).

[7] K. W. Eliceiri et al. “Biological imaging software tools”. In: Nature Methods (2012) (cit. on pp. 1, 2).

[8] Z. Liu and P. J. Keller. “Emerging Imaging and Genomic Tools for Developmental Systems Biology”. In: Developmental Cell (2016) (cit. on p. 1).

[9] E. Meijering et al. “Tracking in cell and developmental biology.” In: Seminars in cell & developmental biology (2009) (cit. on p. 1). [OpenAIRE]

[10] P. Matula et al. “Cell Tracking Accuracy Measurement Based on Comparison of Acyclic Oriented Graphs”. In: PLoS ONE (2015) (cit. on pp. 1, 5, 10). [OpenAIRE]

[11] E. Meijering, O. Dzyubachyk, and I. Smal. “Methods for cell and particle tracking.” In: Methods in enzymology (2012) (cit. on pp. 1, 2). [OpenAIRE]

[12] M. Masˇka et al. “A Benchmark for Comparison of Cell Tracking Algorithms”. In: Bioinformatics (2014) (cit. on pp. 1, 2, 7, 8).

[13] C Held and V. Wiesmann. “Review of free software tools for image analysis of fluorescence cell micrographs”. In: Journal of Microscopy (2015) (cit. on pp. 1, 2).

[14] E. Tu¨retken et al. “Globally Optimal Cell Tracking using Integer Programming”. In: arXiv:1501.05499 (2015) (cit. on pp. 2, 3, 5-8, 10-12).

[15] S. U. Akram et al. “Cell Segmentation Proposal Network for Microscopy Image Analysis”. In: DLMIA (MICCAI-W). 2016 (cit. on pp. 2, 3, 5).

44 references, page 1 of 3
Powered by OpenAIRE Open Research Graph
Any information missing or wrong?Report an Issue