Serial 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 datasets produced. One approach is to reconstruct structures and features of interest in 3D. However, the software programmes 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, accompanied by tutorial videos, for several types of analysis programmes that can be used on raw SBF‐SEM data, although there are more options available than can be covered here. To showcase the programmes, datasets of skeletal muscle from foetal and adult guinea pigs are initially used with procedures subsequently applied to guinea pig cardiac tissue and locust brain. The tissue is processed using the heavy metal protocol developed specifically for SBF‐SEM. Trimmed resin blocks are placed into a Zeiss Sigma SEM incorporating the Gatan 3View and the resulting image stacks are analysed in three different programmes, 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 particular 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 maximize informative output from valuable tissue.
Electron microscopes have been used for decades to image cellular detail at high magnification. However the resulting images are 2‐dimensional. The development of an electron microscope in which we can section tissue in situ means that we can now acquire stacks of images giving us detail in 3‐dimensions. However the challenge with these large datasets is to reconstruct features of interest to form a 3D model. There are a number of computer programs that can be used to do this but they are not intuitive and can be overwhelming for researchers new to them. Here we explain terminology used in the programs and provide a step‐by‐step guide with accompanying videos to help researchers get started with their image analysis and get the best from their data.