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Automated 3-D Tracking of Centrosomes in Sequences of Confocal Image Stacks

Conference ·
OSTI ID:973122
In order to facilitate the study of neuron migration, we propose a method for 3-D detection and tracking of centrosomes in time-lapse confocal image stacks of live neuron cells. We combine Laplacian-based blob detection, adaptive thresholding, and the extraction of scale and roundness features to find centrosome-like objects in each frame. We link these detections using the joint probabilistic data association filter (JPDAF) tracking algorithm with a Newtonian state-space model tailored to the motion characteristics of centrosomes in live neurons. We apply our algorithm to image sequences containing multiple cells, some of which had been treated with motion-inhibiting drugs. We provide qualitative results and quantitative comparisons to manual segmentation and tracking results showing that our motion estimates closely agree with those generated by neurobiology experts.
Research Organization:
Oak Ridge National Laboratory (ORNL)
Sponsoring Organization:
ORNL LDRD Seed-Money
DOE Contract Number:
AC05-00OR22725
OSTI ID:
973122
Country of Publication:
United States
Language:
English

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