A biologists perspective on the challenges in biological image analysis

Pavel Tomancak (MPI Dresden, Germany)

Most primary data in biological research are in the form of images and recent advances in microscopy have brought about orders of magnitude increase in the volume of biological imagery. Since it is no longer possible to draw meaningful conclusions on these vast image datasets by simply inspecting them, computer assisted image analysis is increasingly becoming an indispensable tool for discovery in biological research.

Several fields of computer science, in particular computer vision, deal with analysis of image data. However, the biology application domain poses unique challenges necessitating adjustment of existing algorithms and development on entirely novel approaches. Therefore biologists need to engage in productive collaboration with computer scientists to enable computer assisted reasoning on top of vast biological image datasets.

I will demonstrate how computer vision inspired approaches make a difference in biology on examples from my biological research agenda that focuses on imaging of gene activity in developing biological systems. First I will discuss the acquisition, processing and analysis of massive image datasets using an emerging microscopic imaging modality, the Selective Plane Illumination Microscopy (SPIM) that allows live imaging of entire large biological specimen over extended periods of time with high temporal resolution. Second, I will focus on the reconstruction of the anatomy of biological specimen imaged at the ultimate spatial resolution offered by electron microscopy.

Last, I will put forward an argument that Open Source software platforms are the place where biologists and computer scientists should work collaboratively on solving the challenges posed by these types of datasets.