Visualizations of cells, tissues and organisms are used in biological and medical research since centuries. Recent, unprecedented technical advances in microscopy allow scientists to observe intricate internal details of specimen for days at high magnification and high resolution in 3-dimensions. In addition, a multitude of features can be imaged in parallel, giving rise to large, highly informative datasets. Light-sheet microscopy is an example of a leading microscopy technology which brings about this multitude of advantages for biomedical research.
With these advances in microscopy come technical obstacles. Preparing specimen for light-sheet microscopy, setting up of the microscope recording, and utilizing the resulting images, that can be classified as Big Data, requires expertise spanning from optical physics to engineering, from biology to computer science. In particular, handling the large files resulting from image acquisitions requires specialized software, large computer storage space, and high processing power as the data volume increases. These big data problems have been solved in the scientific community, but require strong expert knowledge in computer software and hardware to be implemented in laboratories.
The Spim4You initiative aimed to explore the need of the scientific community for a professional consulting service concerning light sheet microscopy. In particular, we explored how expert knowledge can be translated to become serviceable to end-users. We aimed initially to transfer the know-how concerning the OpenSPIM light sheet microscope, but also explored the possibility to transfer software solutions concerning this imaging technique that is potentially scalable in longer term. Given the composition of the Spim4You team and the growing need for computational solutions with our customers, software solutions for light-sheet microscopy data proved to be a more useful value proposition. In addition, the emerging sector of pharmaco-microscopy/pharmaco-imaging, that uses imaging based screens for drug target analysis, will prove to be a growing user group.
