Mathematical Imaging Methods for Mitosis Analysis in Live-Cell Phase Contrast Microscopy
Joana Sarah Grah, Jennifer Alison Harrington, Siang Boon Koh, Jeremy, Andrew Pike, Alexander Schreiner, Martin Burger, Carola-Bibiane Sch\"onlieb,, Stefanie Reichelt

TL;DR
This paper introduces a mathematical imaging workflow for detecting and tracking mitotic cells in live-cell phase contrast microscopy, enabling automated analysis of cell division without fluorescent markers.
Contribution
The workflow combines circular Hough transform for mitosis detection with variational tracking methods, providing a new automated approach for live-cell mitosis analysis in phase contrast images.
Findings
Automated mitosis detection and tracking in phase contrast microscopy.
Measurement of mitosis duration and cell fate ratios.
User-friendly MATLAB interface for practical use.
Abstract
In this paper we propose a workflow to detect and track mitotic cells in time-lapse microscopy image sequences. In order to avoid the requirement for cell lines expressing fluorescent markers and the associated phototoxicity, phase contrast microscopy is often preferred over fluorescence microscopy in live-cell imaging. However, common specific image characteristics complicate image processing and impede use of standard methods. Nevertheless, automated analysis is desirable due to manual analysis being subjective, biased and extremely time-consuming for large data sets. Here, we present the following workflow based on mathematical imaging methods. In the first step, mitosis detection is performed by means of the circular Hough transform. The obtained circular contour subsequently serves as an initialisation for the tracking algorithm based on variational methods. It is sub-divided into…
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