A prerequisite for the systems biology analysis of tissues is an accurate digital three-dimensional reconstruction of tissue structure based on images of markers covering multiple scales. Here, we designed a flexible pipeline for the multi-scale reconstruction and quantitative morphological analysis of tissue architecture from microscopy images. Our pipeline includes newly developed algorithms that address specific challenges of thick dense tissue reconstruction. Our implementation allows for a flexible workflow, scalable to high-throughput analysis and applicable to various mammalian tissues. We applied it to the analysis of liver tissue and extracted quantitative parameters of sinusoids, bile canaliculi and cell shapes, recognizing different liver cell types with high accuracy. Using our platform, we uncovered an unexpected zonation pattern of hepatocytes with different size, nuclei and DNA content, thus revealing new features of liver tissue organization. The pipeline also proved effective to analyse lung and kidney tissue, demonstrating its generality and robustness. DOI: http://dx.doi.org/10.7554/eLife.11214.001, eLife digest Understanding how individual cells interact to form tissues in animals and plants is a key problem in cell and developmental biology. To be able to answer this question researchers need to use microscopy to observe the cells in a tissue, extract structural information from the images, and then generate three-dimensional digital models of the tissue. However, the software solutions that are currently available are limited, and reconstructing three-dimensional tissue from microscopy images remains problematic. To meet this challenge, Morales-Navarrete et al. extended the free software platform called MotionTracking, which had been used previously for two-dimensional work. The software now combines a series of new and established algorithms for analysing fluorescence microscopy images that make it possible to identify the different structures that make up a tissue and then create and analyse a three-dimensional model. Morales-Navarrete et al. used the software to analyse liver tissue from mice. The resulting model revealed that liver cells called hepatocytes are arranged in particular zones within the tissue according to their size and DNA content. The software was also applied successfully to analyse lung and kidney tissue, which demonstrates that the approach can be used to create three-dimensional models of a variety of tissues. Morales-Navarrete et al.’s approach can rapidly generate accurate models of larger tissues than were previously possible. Therefore, it provides researchers with a powerful tool to analyse the different features of tissues. This tool will be useful for many areas of research: from understanding of how cells form tissues, to diagnosing diseases based on the changes to features in particular tissues. DOI: http://dx.doi.org/10.7554/eLife.11214.002