A framework for generating realistic synthetic sequences of total internal reflection fluorescence microscopy images
Since generation of reliable ground truth annotation of fluorescence microscopy sequences is usually a laborious and expensive task, many proposed detection and tracking methods have been evaluated using synthetic data with known ground truth. However, differences between real and synthetic images may lead to inaccurate judgment about the performance of an algorithm. In this paper, we present a framework for generating realistic synthetic sequences of total internal reflection fluorescence microscope (TIRFM) through simulation of the image formation process and accurate measurement and dynamic models. The sequences generated using this framework appropriately reflect the complexities existing in real TIRFM sequences.