Improvement of a subviral particle tracker by the use of a LAP-Kalman-algorithm - Rausch Andreas; Müller Dennis; Schanze Thomas (Current Directions in Biomedical Engineering, 2016)
Automated detection and tracking of subviral particles is a promising method to obtain insights in complicated virus-cell interactions. This paper describes the implementation of a linear assignment problem solver and a Kalman-filter in an existing particle tracking algorithm. Two different simulated image sequences are used for the evaluation of the algorithms. Tracking and detection results of the new implemented solver are compared to the results of the original algorithm. The improved algorithm is able to improve the results by closing gaps in the particle tracks.