Single cell tracking based on Voronoi partition via stable matching

Abstract

Live-cell imaging is an important technique to study cell migration and proliferation as well as image-based profiling of drug perturbations over time. To gain biological insights from live-cell imaging data, it is necessary to identify individual cells, follow them over time and extract quantitative information. However, since often biological experiment does not allow the high temporal resolution to reduce excessive levels of illumination or minimize unnecessary oversampling to monitor long-term dynamics, it is still a challenging task to obtain good tracking results with coarsely sampled imaging data. To address this problem, we consider cell tracking problem as "stable matching problem" and propose a robust tracking method based on Voronoi partition which adapts parameters that need to be set according to the spatio-temporal characteristics of live cell imaging data such as cell population and migration. We demonstrate the performance improvement provided by the proposed method using numerical simulations and compare its performance with proximity-based tracking and nearest neighbor-based tracking.

Three dimensional and four dimensional live imaging to study mechanisms of progressive neurodegeneration

“…Using fiducial marks on the bottom of the plate and custom software, it collects information from individual cells by automatically returning to precisely the same microscope field repetitively for days to months, so that fluorescence signals from biosensors introduced into individual cells can be collected at regular intervals and analyzed offline ( 43 ). This provides for temporal analysis of neurons because automated analysis programs that can be employed through open-source python packages can segment and identify individual cells in each image, assign them a unique identifying number, track them over the imaging time course, extract fluorescence signals from labels in each cell, and determine cellular characteristics in subsequent images ( 30 , 31 , 36 , 37 , 39 , 40 , 41 , 44 ). The hardware to execute robotic microscopy is commercially available through vendors that sell automated confocal microscope systems that can be integrated with automated cell culture incubators to achieve automated longitudinal imaging.…”