AUTHOR=Titze Benjamin , Genoud Christel , Friedrich Rainer W. TITLE=SBEMimage: Versatile Acquisition Control Software for Serial Block-Face Electron Microscopy JOURNAL=Frontiers in Neural Circuits VOLUME=12 YEAR=2018 URL=https://www.frontiersin.org/journals/neural-circuits/articles/10.3389/fncir.2018.00054 DOI=10.3389/fncir.2018.00054 ISSN=1662-5110 ABSTRACT=

We present SBEMimage, an open-source Python-based application to operate serial block-face electron microscopy (SBEM) systems. SBEMimage is designed for complex, challenging acquisition tasks, such as large-scale volume imaging of neuronal tissue or other biological ultrastructure. Advanced monitoring, process control, and error handling capabilities improve reliability, speed, and quality of acquisitions. Debris detection, autofocus, real-time image inspection, and various other quality control features minimize the risk of data loss during long-term acquisitions. Adaptive tile selection allows for efficient imaging of large tissue volumes of arbitrary shape. The software’s graphical user interface is optimized for remote operation. In its user-friendly viewport, tile grids covering the region of interest to be acquired are overlaid on previously acquired overview images of the sample surface. Images from other sources, e.g., light microscopes, can be imported and superimposed. SBEMimage complements existing DigitalMicrograph (Gatan Microscopy Suite) installations on 3View systems but permits higher acquisition rates by interacting directly with the microscope’s control software. Its modular architecture and the use of Python/PyQt make SBEMimage highly customizable and extensible, which allows for fast prototyping and will permit adaptation to a wide range of SBEM systems and applications.