CASUS Institute Seminar, Joel Johnsson, MPI-CBG
Modern fluorescence microscopy techniques allow imaging deep inside tissues at high spatial and temporal resolution. This produces enormous amounts of data that are essential for understanding biological structures and spatiotemporal processes. However, the sheer volume of data often places restrictive requirements on downstream processing algorithms necessary to extract meaningful information. In order to address this issue, the Adaptive Particle Representation (APR) has been developed as an alternative to uniform pixel grids. The APR optimally re-adapts the local sampling density based on the content of the image, and has been shown to yield orders of magnitude reductions to the memory and computational operations required to process, visualize and store fluorescence microscopy images (Cheeseman et al, 2018).
In the first part of the seminar I will introduce the ideas and concepts behind the APR, show examples of image processing and visualization using the APR, and briefly touch on possibilities for future developments. The second part of the seminar will be more interactive, and can take several directions depending on the interests of the audience. This may include, for example, a live demonstration of our software libraries, in-depth discussion of data structures and algorithms for the APR, or possibilities and opportunities to get involved in the APR as a user and/or developer.