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.
|Title of host publication||Irish Machine Vision & Image Processing Conference proceedings 2016|
|Number of pages||8|
|Publication status||Published - 25 Aug 2016|
|Event||Irish Machine Vision and Image Processing Conference - NUIG , Galway, United Kingdom|
Duration: 24 Aug 2016 → 26 Aug 2016
Conference number: 5th
|Conference||Irish Machine Vision and Image Processing Conference|
|Period||24/08/2016 → 26/08/2016|
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Student thesis: Doctoral Thesis › Doctor of PhilosophyFile