The essential reason to use imaging techniques in the life sciences is the generation of data to answer biological questions. This aim is in general accomplished by using a combination of image acquisition and advanced image analysis.
Conventional imaging follows the constant interaction of an operator, searching for suitable objects or regions of interest (ROIs) on the sample, with the microscopy system and making appropriate optimal acquisition settings to decisively scan these ROIs. Due to the nature of such a manually defined experimental workflow, only a manageable number of ROIs can be precisely localized, and the acquisition of ROIs requires a lot of time.
The rare event detection workflow performed by applying Autonomous Microscopy powered by Aivia works completely autonomous after the setup at the beginning of the experiment. As soon as the experiment is started, no human intervention is required from a low-resolution pre-scan to the detection of rare events and the acquisition and storage of the high-resolution 3D images. The clear benefit is the high speed of this process and the large number of detected rare events during the experiment
Autonomous microscopy enables the automated detection of such ROIs or rare events (REs) without the need for human interaction and, thus, the complete automation of complex microscopic workflows. Within this autonomous workflow, low-resolution 2-dimensional (2D) overview images are generated in a first step, which are immediately transferred to the connected AI-based image processing (Aivia) system. This detects the rare events, previously defined by the operator, by means of a pixel classifier and sends the rare event coordinates back to the imaging system, which scans the rare events according to the operator's specifications, such as high-resolution and 3-dimensional (3D) data stacks. In this way, the generated data are:
- highly specific to the object of interest,
- available in a statistically relevant number due to automation.
The highly specific scanning of rare events massively increases the overall quality of the acquired data, as only data really of interest is obtained. This approach ensures target scanning with an accuracy of up to 90 % of all existing rare events. At the same time, a highly economical operation of the microscope system is achieved, because there are no long "idle times" due to time-consuming and, thus, costly manual searches for rare events.
Besides highly specific rare event scanning, autonomous microscopy enables the acquisition of data completely independent of the rare events objectives. Objects of interest can be scanned in a target-oriented manner, which, on the one hand, massively prevents the generation of junk data and, on the other hand, provides the acquired data in a highly qualitative manner for subsequent image analysis. These advantages are achievable, because the acquired object is always centrally located in the field of view (FOV) of the scan area.
Reproducibility is one of the key elements of trustworthy life science research. Autonomously working experiment sequences can be restored at any time, equipped with the appropriate versioning, and run again with exactly the same settings. This process ensures a reproducibility that could never be achieved by a manual setup imaging procedures for experiments.
Furthermore, highly complex microscopy workflows can be set up and automated, making advanced applications accessible that could not be addressed before at all or only with considerable manual effort.