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 language | English |
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Title of host publication | Irish Machine Vision & Image Processing Conference proceedings 2016 |
Pages | 33-40 |
Number of pages | 8 |
Publication status | Published - 25 Aug 2016 |
Event | 18th Irish Machine Vision and Image Processing Conference 2016 - NUIG , Galway, United Kingdom Duration: 24 Aug 2016 → 26 Aug 2016 |
Conference
Conference | 18th Irish Machine Vision and Image Processing Conference 2016 |
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Abbreviated title | IMVIP |
Country/Territory | United Kingdom |
City | Galway |
Period | 24/08/2016 → 26/08/2016 |
Fingerprint
Dive into the research topics of 'Analysis of variable-order interacting multiple model algorithms for cell tracking'. Together they form a unique fingerprint.Student theses
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Detection and tracking of cells and focal adhesions in microscopy images
Lomanov, K. (Author), Miller, P. (Supervisor) & Martinez del Rincon, J. (Supervisor), Dec 2020Student thesis: Doctoral Thesis › Doctor of Philosophy
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