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A Multiple Model Probability Hypothesis Density Tracker for Time-Lapse Cell Microscopy Sequences

Date

Authors

Rezatofighi, Seyed

Gould, Stephen

Vo, Ba-Ngu

Mele, Katarina

Hughes, William E

Hartley, Richard

Publisher

Springer

Abstract

Quantitative analysis of the dynamics of tiny cellular and subcellular structures in time-lapse cell microscopy sequences requires the development of a reliable multi-target tracking method capable of tracking numerous similar targets in the presence of h

Keywords

Keywords: Biological applications; Maneuvering motion; Model probabilities; Multi-target tracking; Recursion equations; Subcellular structure; Total internal reflection fluorescence microscopy; Transition probability matrix; Data processing; Medical imaging; Refrac

URI

http://hdl.handle.net/1885/65967

Collections

ANU Research Publications

Source

Lecture Notes in Computer Science (LNCS)

Type

Journal article

DOI

10.1007/978-3-642-38868-2_10

Restricted until

2037-12-31

Downloads

File

Description

01_Rezatofighi_A_Multiple_Model_Probability_2013.pdf (484.18 KB)