The Saalfeld lab is interested in the design and development of methods and software for scalable automatic image analysis and collaborative manual and semi-automatic image annotation.
Neural Connectivity Reconstruction at Scale
The central brain of Drosophila melanogaster consists of ∼100,000 neurons and fits into a box of approximately 500×400×200 μm3. Individual neurons can span processes across distances of several 100 μm, their individual projections, however, can be as thin as 40 nm in diameter. Today, only Electron Microscopy (EM) offers a sufficient combination of spatial resolution, field of view, and throughput to image a biological nervous system of this size in its entirety and to potentially enable the reconstruction of the complete wiring diagram. At Janelia, we are using two complementary EM imaging techniques, (1) serial block-face scanning combined with ion beam milling (FIB-SEM, Hess lab, FlyEM project team) which generates isotropic image data at a resolution of typically 8 nm3 per voxel, and (2) serial section transmission imaging (ssTEM, Bock and Fetter labs) generating non-isotropic image data of typically 4×4×40 nm3 per voxel. At that resolution, a Drosophila brain fits into ∼40–80 trillion voxels.
Connectivity analysis from Electron Microscopy (EM) images requires both efficient automation and manual proofreading. Current state-of-the-art automatic image analysis methods have high demands on data quality to deliver satisfying results within reasonable time. Both FIB-SEM and ssTEM, however, come with their own set of preparation and imaging artifacts that make automatic and manual reconstruction a non-trivial endeavour. We are developing new automatic methods and user interfaces to compensate for these artifacts and to enable high quality automatic connectivity reconstruction from compromised data and complementary imaging modalities. In order to cope with the scale of the project, we pay significant attention to software design with focus on efficiency, scalability and re-usability.