Automatic detection and analysis of cell motility in phase-contrast time-lapse images using a combination of maximally stable extremal regions and Kalman filter approaches.

Publisher: Published for the Royal Microscopical Society by Blackwell Scientific Publications Country of Publication: England NLM ID: 0204522 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1365-2818 (Electronic) Linking ISSN: 00222720 NLM ISO Abbreviation: J Microsc Subsets: MEDLINE

Original Publication: Oxford, Published for the Royal Microscopical Society by Blackwell Scientific Publications.

Cell Movement*; Automation, Laboratory/*methods ; Microscopy, Phase-Contrast/*methods ; Time-Lapse Imaging/*methods; Image Processing, Computer-Assisted/methods

Phase-contrast illumination is simple and most commonly used microscopic method to observe nonstained living cells. Automatic cell segmentation and motion analysis provide tools to analyze single cell motility in large cell populations. However, the challenge is to find a sophisticated method that is sufficiently accurate to generate reliable results, robust to function under the wide range of illumination conditions encountered in phase-contrast microscopy, and also computationally light for efficient analysis of large number of cells and image frames. To develop better automatic tools for analysis of low magnification phase-contrast images in time-lapse cell migration movies, we investigated the performance of cell segmentation method that is based on the intrinsic properties of maximally stable extremal regions (MSER). MSER was found to be reliable and effective in a wide range of experimental conditions. When compared to the commonly used segmentation approaches, MSER required negligible preoptimization steps thus dramatically reducing the computation time. To analyze cell migration characteristics in time-lapse movies, the MSER-based automatic cell detection was accompanied by a Kalman filter multiobject tracker that efficiently tracked individual cells even in confluent cell populations. This allowed quantitative cell motion analysis resulting in accurate measurements of the migration magnitude and direction of individual cells, as well as characteristics of collective migration of cell groups. Our results demonstrate that MSER accompanied by temporal data association is a powerful tool for accurate and reliable analysis of the dynamic behaviour of cells in phase-contrast image sequences. These techniques tolerate varying and nonoptimal imaging conditions and due to their relatively light computational requirements they should help to resolve problems in computationally demanding and often time-consuming large-scale dynamical analysis of cultured cells.
(© 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.)

Keywords: Automatic cell segmentation; Kalman filter; MSER; cell migration; phase-contrast microscopy; tracking

Date Created: 20131128 Date Completed: 20140716 Latest Revision: 20191210

20250114

10.1111/jmi.12098

24279418