Bioimage analysis platforms to track cells in large samples

In the last decade or so, the rise of quantitative approaches in biological imaging has spurred new demands for access to image analysis techniques. Various initiatives, such as NEUBIAS, have played a crucial role in shaping a new position in academic research: the bioimage analysts. These experts bridge the needs of a research project with existing tools and techniques in bioimage analysis, creating bespoke analysis pipelines, adapting, or developing tools to address specific questions in Biology. Bioimage analysis core facilities are currently emerging as dedicated structures that house analysts and provide services to a broad scientific community.

In the first part of this talk, I will present briefly the Image Analysis Hub of the Institut Pasteur, a core facility dedicated to services in Bioimage Analysis. Established early 2018, we were one of the first core facilities dedicated to bioimage analysis. I will outline the services we deliver, what we don't oPer, and the reasoning behind these choices. I will discuss our current organizational structure, useful policies we have implemented, and the lessons we've learned in establishing the core.

An important component that facilitates our work and helps honing our skills is the development of innovative bioimage analysis platforms: they are scientific software that address a class of applications in biology. I will discuss in a second part some of the tools we have built and maintain, such as TrackMate, MaMuT and Mastodon, that are focused on cell and organelle tracking. I will discuss the challenges they address, mainly going towards very large samples, integrating AI algorithms in tracking pipelines, and delivering a responsive interface facilitating data exploration, curation and analysis in the context of tracking. Finally, I will explain how their development is aligned with scientific added-value for our users.