Segmentation and tracking of migrating cells in videomicroscopy with parametric active contours: a tool for cell-based drug testing

By Christophe Zimmer, Elisabeth Labruyere, Vannary Meas-Yedid, Nancy Guillen, Jean-Christophe Olivo-Marin. 2002

322 citations recorded by the source corpus.

Subfields: Biophysics, Cell Biology, Computer Vision and Pattern Recognition, Media Technology, Medical Imaging

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biophysics

1. Erik H. W. Meijering
2. Fuyong Xing
3. Lin F. Yang
4. Oleh Dzyubachyk
5. Houqiang Li
6. Xiaodong Yang
7. Xiaobo Zhou
8. Carlos Ortiz-de-Solorzano

In Cell Biology

1. Sally Temple
2. B. Roysam
3. Erik H. W. Meijering
4. Oleh Dzyubachyk
5. Ihor Smal
6. W. V. van Cappellen

In Computer Vision and Pattern Recognition

1. Lin F. Yang
2. Fuyong Xing
3. Houqiang Li
4. Erik H. W. Meijering
5. Oleh Dzyubachyk
6. Xiaodong Yang
7. Joakim Jaldén
8. Klas E. G. Magnusson

In Media Technology

1. Lin F. Yang
2. Fuyong Xing
3. Oleh Dzyubachyk
4. Erik H. W. Meijering
5. Houqiang Li
6. Xiaodong Yang
7. Xiaobo Zhou
8. Omar Al-Kofahi

In Medical Imaging

1. Lin F. Yang
2. Fuyong Xing
3. Joakim Jaldén
4. Klas E. G. Magnusson
5. B. Roysam
6. Oren Z. Kraus
7. Brendan J. Frey

Citations in the corpus

• A benchmark for comparison of cell tracking algorithms (2014, methodology): “After the ISBI 2013 workshop, the organizing committee confirmed the accuracy of the submitted results and compiled the final rankings presented in this article.”
• Automated Cell Lineage Construction: A Rapid Method to Analyze Clonal Development Established with Murine Neural Progenitor Cells (2006, background): “19-21 In cases where obtaining the exact cell boundary is not critical, the mean-shift algorithm 22 gives a fast solution for tracking cells.”
• Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review (2016, methodology): “[246] have introduced a new edge map, which is calculated for each snake, to handle weak object boundaries, and successfully applied it to cell segmentation and tracking in phase-contrast microscopy images.”
• Cell Population Tracking and Lineage Construction with Spatiotemporal Context (2007, methodology): “The region energy Eregion is based on the Bayesian region-competition framework ( Zhu and Yuille, 1996; Cremers et al., 2007):”
• Nuclei Segmentation Using Marker-Controlled Watershed, Tracking Using Mean-Shift, and Kalman Filter in Time-Lapse Microscopy (2006, methodology): “In this method, the tracking result of the former frame is used to initiate the parameters in the current frame and 100% tracking accuracy based on this method has been reported [ 4 ].”
• Tracking of migrating cells under phase-contrast video microscopy with combined mean-shift processes (2005, methodology): “Indeed, the result of the model adjustment process in frame -1 is used to initialize the process in frame [ 5 ], [10], [14], [15], [19], [20].”
• Tracking in cell and developmental biology. (2009, background): “If these conditions are not met, or they need to be compromised for practical reasons, more sophistication is required, such as the use of gradient-vector flows [36, 52], estimated cell dynamics [39, 42], and special procedures to handle cell contacts, divisions, appearances, and disappearances [41,”
• An Objective Comparison of Cell Tracking Algorithms (2017, unknown): “The methods range from simple thresholding 9,10 , hysteresis thresholding 11 , edge detection 12 , or shape matching 13,14 , to more sophisticated region growing 15–17 , machine learning 18,19 , or energy minimization 20–26 approaches.”
• Multiple Nuclei Tracking Using Integer Programming for Quantitative Cancer Cell Cycle Analysis (2010, background): “, the cell clustering, division, and fast migration, is nontrivial and will rapidly increase computation time [11], [16].”