A multiple hypothesis based method for particle tracking and its extension for cell segmentation

Liang Liang, Hongying Shen, Panteleimon Rompolas, Valentina Greco, Pietro De Camilli, James S. Duncan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

In biological studies, it is often required to track thousands of small particles in microscopic images to analyze underlying mechanisms of cellular and subcellular processes which may lead to better understanding of some disease processes. In this paper, we present an automatic particle tracking method and apply it for analyzing an essential subcellular process, namely clathrin mediated endocytosis using total internal reflection microscopy. Particles are detected by using image filters and subsequently Gaussian mixture models are fitted to achieve sub-pixel resolution. A multiple hypothesis based framework is designed to solve data association problems and handle splitting/merging events. The tracking method is demonstrated on synthetic data under different scenarios and applied to real data. We also show that, by equipping with a cell detection module, the method can be extended straightforwardly for segmenting cell images taken by two-photon excitation microscopy.

Original languageEnglish (US)
Title of host publicationInformation Processing in Medical Imaging - 23rd International Conference, IPMI 2013, Proceedings
Pages98-109
Number of pages12
DOIs
StatePublished - 2013
Externally publishedYes
Event23rd International Conference on Information Processing in Medical Imaging, IPMI 2013 - Asilomar, CA, United States
Duration: Jun 28 2013Jul 3 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7917 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd International Conference on Information Processing in Medical Imaging, IPMI 2013
Country/TerritoryUnited States
CityAsilomar, CA
Period6/28/137/3/13

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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