YIT

Automatic tracking of cells in time-lapse microscopy is required to investigate a multitude of biological questions. To limit manipulations during cell line preparation and phototoxicity during imaging, brightfield imaging is often considered. Since the segmentation and tracking of cells in brightfield images is considered to be a difficult and complex task, a number of software solutions have been already developed. However, the software’s quality assessment is barely possible due to the lack of broadly available benchmarks and comparison methodologies. To overcome this issue in the context of yeast research, we provide an annotated benchmark of yeast images. It covers variety of situations including i) single cells and small colonies ii) colony translations and merging iii) big colonies with heavily clustered cells. Moreover, we provide an Evaluation Platform - a tool based on mathematical framework - that facilitates the analysis of algorithm results and compares it with other available tools.

Find more details on external pageYIT project homepage.