Tracking of migrating cells under phase-contrast video microscopy with combined mean-shift processes

By Olivier Debeir, Philippe Van Ham, Robert Kiss, Christine Decaestecker. IEEE Transactions on Medical Imaging, 2005

322 citations recorded by the source corpus.

Subfields: Biophysics, Computer Vision and Pattern Recognition, Immunology

View Paper: https://www.semanticscholar.org/paper/861fa32053e4a60fcb70b843e0fb5145ce83d3b0

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Citations in the corpus

Cell Population Tracking and Lineage Construction with Spatiotemporal Context (2007, methodology): “While cell fusion occurs in specific cell types (e.g., activated macrophages and osteoclasts), it does not normally occur for the cell types studied in this paper, nor in many other studies (Zimmer et al., 2002; Mukherjee et al., 2004; Zhang et al., 2004; Yang et al., 2005a; Zimmer and Olivo-Marin, ”
Coupled minimum-cost flow cell tracking for high-throughput quantitative analysis (2011, methodology): “in [10] track cell centroids without segmentation by updating the centroid locations using the mean-shift algorithm; this algorithm depends heavily on the accuracy of the centroid localization since the tracking results degrade as the centroids start to drift.”
Multiple Nuclei Tracking Using Integer Programming for Quantitative Cancer Cell Cycle Analysis (2010, unknown): “Mean-shift [9], [10], parametric active contour [11]–[13], and level set [14], [15] are the widely used tracking approaches from this category.”
Tracking in cell and developmental biology. (2009, methodology): “A similar argument applies when using so-called meanshift processes to iteratively compute cell positions [47,48].”
On the digital trail of mobile cells (2006, methodology): “These constraints can be exploited to discriminate cells that touch or even partly occlude each other, such as elliptical leukocytes [8] or Candida yeast cells [23], but as discussed above, are not applicable to highly plastic amoebae [9] or cancer cells [21].”
Nuclei Segmentation Using Marker-Controlled Watershed, Tracking Using Mean-Shift, and Kalman Filter in Time-Lapse Microscopy (2006, methodology): “Original watershed directly uses region minimums or ultimate eroded points (UEPs) as starting points [1], [8].”
Advanced Level-Set-Based Cell Tracking in Time-Lapse Fluorescence Microscopy (2010, methodology): “One example of this type of tracking is the meanshift process [ 33 ], which works well in case of tracking cells of known shape showing relatively small displacements between frames.”
Segmentation and Shape Tracking of Whole Fluorescent Cells Based on the Chan–Vese Model (2013, background): “When the precise cell boundaries are not required, the mean-shift processes can be applied to track cell centroids [14].”
Automated and semi‐automated cell tracking: addressing portability challenges (2011, methodology): “Methods from the first group allow the combination of cell detection and tracking stages, but these methods rely on smooth cell motions (Debeir et al. , 2005; Padfield et al. , 2010).”