Structure-resolving index: an efficient criterion for ending image acquisition in super-resolution localization microscopy

Abstract

In super-resolution localization microscopy, a final super-resolution image is built upon a huge amount of raw image frames (typically >10,000). To guarantee the quality of a final super-resolution image, researchers tend to collect as many raw images as possible, leading to excess data volume, which causes a significant waste of data acquisition time and computation resources. Here we present the structure-resolving index (SRI), an efficient criterion to end image acquisition automatically. Simulated and experimental data show that SRI can be used as a superior ending criterion to minimize the acquisition of excess data volume while ensuring the resolving ability of a final super-resolution image.