AbstractSerial block face scanning electron microscopy (SBF-SEM) is a relatively new technique that allows the acquisition of serially sectioned, imaged and digitally aligned ultrastructural data. There is a wealth of information that can be obtained from the resulting image stacks but this presents a new challenge for researchers - how to computationally analyse and make best use of the large data sets produced. One approach is to reconstruct structures and features of interest in 3D. However the software programs can appear overwhelming, time consuming and not intuitive for those new to image analysis. There are a limited number of published articles that provide sufficient detail on how to do this type of reconstruction. Therefore the aim of this paper is to provide a detailed step-by-step protocol, videos and explanation on the types of analysis and programs that can be used. To showcase the programs, skeletal muscle from fetal and adult guinea pigs were used. The tissue was processed using the heavy metal protocol developed specifically for SBFSEM. Trimmed resin blocks were placed into a Zeiss Sigma SEM incorporating the Gatan 3View and the resulting image stacks were analysed in 3 different programs, Fiji, Amira and MIB, using a range of tools available for segmentation. The results from the image analysis comparison show that the analysis tools are often more suited to a type of structure. For example larger structures, such as nuclei and cells, can be segmented using interpolation, which speeds up analysis; single contrast structures, such as the nucleolus, can be segmented using the contrast-based thresholding tools. Knowing the nature of the tissue and its specific structures (complexity, contrast, if there are distinct membranes, size) will help to determine the best method for reconstruction and thus maximising output from valuable tissue.
Plasma Cleaning Improves the Image Quality of Serial Block-face Scanning Electron Microscopy (SBFSEM) Volumetric Data Sets
