Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
A survey of thresholding techniques
Computer Vision, Graphics, and Image Processing
Feature Point Correspondence in the Presence of Occlusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Noniterative Greedy Algorithm for Multiframe Point Correspondence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Online Tracking of Migrating and Proliferating Cells Imaged with Phase-Contrast Microscopy
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Coupled Minimum-Cost Flow Cell Tracking
IPMI '09 Proceedings of the 21st International Conference on Information Processing in Medical Imaging
Efficient Mean Shift Particle Filter for Sperm Cells Tracking
CIS '09 Proceedings of the 2009 International Conference on Computational Intelligence and Security - Volume 01
Microscope Image Processing
Cell Tracking in Video Microscopy Using Bipartite Graph Matching
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Cell image analysis: Algorithms, system and applications
WACV '11 Proceedings of the 2011 IEEE Workshop on Applications of Computer Vision (WACV)
Automating the tracking of lymph nodes in follow-up studies of thoracic CT images
Computer Methods and Programs in Biomedicine
A review of thresholding strategies applied to human chromosome segmentation
Computer Methods and Programs in Biomedicine
Lung tumor segmentation in PET images using graph cuts
Computer Methods and Programs in Biomedicine
Segmentation of pituitary adenoma: A graph-based method vs. a balloon inflation method
Computer Methods and Programs in Biomedicine
Computer Methods and Programs in Biomedicine
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Automated visual tracking of cells from video microscopy has many important biomedical applications. In this paper, we track human monocyte cells in a fluorescent microscopic video using matching and linking of bipartite graphs. Tracking of cells over a pair of frames is modeled as a maximum cardinality minimum weight matching problem for a bipartite graph with a novel cost function. The tracking results are further refined using a rank-based filtering mechanism. Linking of cell trajectories over different frames are achieved through composition of bipartite matches. The proposed solution does not require any explicit motion model, is highly scalable, and, can effectively handle the entry and exit of cells. Our tracking accuracy of (97.97+/-0.94)% is superior than several existing methods [(95.66+/-2.39)% [11], (94.42+/-2.08)% [20], (81.22+/-5.75)% [13], (78.31+/-4.70)% [14]] and is highly comparable (98.20+/-1.22)% to a recently published algorithm [26].