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

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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
EventIrish Machine Vision and Image Processing Conference - NUIG , Galway, United Kingdom
Duration: 24 Aug 201626 Aug 2016
Conference number: 5th
http://optics.nuigalway.ie/IMVIP2016/

Conference

ConferenceIrish Machine Vision and Image Processing Conference
Abbreviated titleIMVIP
CountryUnited Kingdom
CityGalway
Period24/08/201626/08/2016
Internet address

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