Analysis of variable-order interacting multiple model algorithms for cell tracking

K. Lomanov, J. Martinez del Rincon, P. Miller, H. Gribben

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

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Abstract

In this paper we propose a modification of the Interacting Multiple Model (IMM) filter to effectively track complex dynamics in cell images. Our solution proposes a more efficient use and combination of the multiple Kalman filter estimations that lead to a performance improvement in multi-cell sequences, with an increase of up to 10% in the recall value, compared to the classic IMM. First and second order models are evaluated in the scope of cell migration. The system is evaluated and compared against a baseline using 3D synthetic confocal microscopy images, where cells behave realistically according to actual cell trajectories extracted from real sequences in biology. 
Original languageEnglish
Title of host publicationIrish Machine Vision & Image Processing Conference proceedings 2016
Pages33-40
Number of pages8
Publication statusPublished - 25 Aug 2016
Event18th Irish Machine Vision and Image Processing Conference 2016 - NUIG , Galway, United Kingdom
Duration: 24 Aug 201626 Aug 2016

Conference

Conference18th Irish Machine Vision and Image Processing Conference 2016
Abbreviated titleIMVIP
Country/TerritoryUnited Kingdom
CityGalway
Period24/08/201626/08/2016

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