Title: Multiple cell tracking by generalised labelled multi-Bernoulli filter

Authors: Jian Shi; Ming-Li Lu

Addresses: School of Electrical and Automatic Engineering, Changshu Institute of Technology, Changshu, Suzhou Shi, Jiangsu Sheng, China ' School of Electrical and Automatic Engineering, Changshu Institute of Technology, Changshu, Suzhou Shi, Jiangsu Sheng, China

Abstract: Cell detection and tracking in microscopy images are of great importance to medical research and related fields. In this paper, a generalised labelled multi-Bernoulli (GLMB) track-before-detect (TBD) filter is proposed for the tracking of multiple cells. In this filter, GLMB based on random finite set (RFS) theory is used to jointly estimate the positions and the numbers of cells in images, and TBD is adopted to track cells without explicit detection step. The experimental results indicate that the proposed method can accurately discover cells and maintain their tracks in low contrast image sequences.

Keywords: cell tracking; random finite set; track-before-detect; generalised labelled multi-Bernoulli.

DOI: 10.1504/IJCAT.2019.103296

International Journal of Computer Applications in Technology, 2019 Vol.61 No.4, pp.273 - 277

Received: 01 Feb 2019
Accepted: 02 Mar 2019
Published online: 25 Oct 2019 *

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