A novel multiple particle tracking algorithm for noisy in vivo data by minimal path optimization within the spatio-temporal volume

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Title of host publicationProceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009
DatePublished - 1 Jan 2009
Pages1158-1161
Number of pages4
Original languageEnglish

Abstract

Automated tracking of fluorescent particles in living cells is vital for subcellular stoichoimetry analysis [1, 2]. Here, a new automatic tracking algorithm is described to track multiple particles, based on minimal path optimization. After linking feature points frame-by-frame, spatio-temporal data from time-lapse microscopy are combined together to construct a transformed 3D volume. The trajectories are then generated from the minimal energy path as defined by the solution of the time-dependent partial differential equation using a gray weighted distance transform dynamic programming method. Results from simulated and experimental data demonstrate that our novel automatic method gives sub-pixel accuracy even for very noisy images.

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