Title :
Tracking virus particles in fluorescence microscopy images using two-step multi-frame association
Author :
Jaiswal, A. ; Godinez, W.J. ; Eils, R. ; Lehmann, M.J. ; Rohr, K.
Author_Institution :
Dept. Bioinf. & Functional Genomics, Univ. of Heidelberg, Heidelberg, Germany
Abstract :
Automatic fluorescent particle tracking is an essential task to study the dynamics of a large number of biological structures at a sub-cellular level. We have developed a two-step multi-frame association finding algorithm which is based on a temporally semi-global formulation as well as combines a spatially global and a spatially local approach. Using this multi-frame association finding algorithm we have developed a probabilistic tracking approach based on the Kalman filter. We have successfully applied the approach to synthetic as well as real microscopy image sequences of ALV virus particles and quantified the performance. We found that the proposed approach outperforms previous approaches.
Keywords :
Kalman filters; biomedical optical imaging; cellular biophysics; fluorescence; image sequences; medical image processing; microorganisms; optical microscopy; probability; ALV virus particles; Kalman filter; automatic fluorescent particle tracking; avian leukosis virus particles; biological structures; fluorescence microscopy imaging; multiframe association finding algorithm; probabilistic tracking approach; real microscopy image sequences; subcellular level; temporally semiglobal formulation; two-step multiframe association; two-step multiframe association finding algorithm; virus particle tracking; Image sequences; Kalman filters; Microscopy; Particle tracking; Probabilistic logic; Signal to noise ratio; Tracking; Kalman filter; Virus particle tracking; multi-frame association;
Conference_Titel :
Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4577-1857-1
DOI :
10.1109/ISBI.2012.6235635
