Tech Exchange with Argolight

Arnaud Royon, CEO and co-founder of Argolight, will present on "Instrument quality control in fluorescence bio-imaging".

Abstract

One of the core facilities’ duties is to provide end-users, usually researchers in life sciences, with a fleet of microscopes that maintain performance levels compatible with their experiments. This is challenging because microscopes inherently introduce biases in the images and because their performance tends to fluctuate or deteriorate over time due to misuse, age, environmental condition, etc. This is especially true for high end imaging systems such as confocal or super-resolution microscopes.

At the age of big data, artificial intelligence, machine learning, and predictive models, it is essential to perform quality control and quality assurance at every step of a bio-imaging experiment: from sample preparation to imaging system, and image analysis, to extract accurate biological information. Feeding the image analysis algorithms with corrupted image data gives rise to the well-known adage: “garbage in, garbage out”.

To obtain quantitative and reproducible data, assessing the performance of fluorescence microscopes is a prerequisite before any imaging campaign. This helps to identify, measure and eventually correct the different biases they may introduce. For example, evaluating system co-registration is important before any co-localization study; System field uniformity and intensity response before any study where intensity in the image matters; Spatial resolution before any study aiming at counting objects close to each other, etc.

This tech talk aims to:

• explain the importance of instrument quality control in fluorescence bio-imaging,
• provide examples of how microscope biases can alter biological interpretations,
• present the actions to prevent or to correct these biases.