Recent advances in electron microscopy have enabled the imaging of single cells in 3D at nanometer length scale resolutions. An uncharted frontier for in silico biology is the ability to simulate cellular processes using these observed geometries. Enabling such simulations requires watertight meshing of electron micrograph images into 3D volume meshes, which can then form the basis of computer simulations of such processes using numerical techniques such as the finite element method. In this paper, we describe the use of our recently rewritten mesh processing software, GAMer 2, to bridge the gap between poorly conditioned meshes generated from segmented micrographs and boundary marked tetrahedral meshes which are compatible with simulation. We demonstrate the application of a workflow using GAMer 2 to a series of electron micrographs of neuronal dendrite morphology explored at three different length scales and show that the resulting meshes are suitable for finite element simulations. This work is an important step towards making physical simulations of biological processes in realistic geometries routine. Innovations in algorithms to reconstruct and simulate cellular length scale phenomena based on emerging structural data will enable realistic physical models and advance discovery at the interface of geometry and cellular processes. We posit that a new frontier at the intersection of computational technologies and single cell biology is now open.

Recent advances in electron microscopy have, for the first time, enabled imaging of single cells in 3D at a nanometer length scale resolution. An uncharted frontier for in silico biology is the ability to simulate cellular processes using these observed geometries. Enabling such simulations will require a system for going from electron micrographs to 3D volume meshes, which can then form the basis of computer simulations of such processes using numerical techniques such as the Finite Element Method (FEM). In this paper, we develop an end-to-end pipeline for this task by adapting and extending computer graphics mesh processing and smoothing algorithms. Our workflow makes use of our recently rewritten mesh processing software, GAMer 2, which implements several mesh conditioning algorithms and serves as a platform to connect different pipeline steps. We apply this pipeline to a series of electron micrographs of neuronal dendrite morphology explored at three different length scales and demonstrate that the resultant meshes are suitable for finite element simulations. Our pipeline, which consists of free and open-source community driven tools, is a step towards routine physical simulations of biological processes in realistic geometries. We posit that a new frontier at the intersection of computational technologies and single cell biology is now open. Innovations in algorithms to reconstruct and simulate cellular length scale phenomena based on emerging structural data will enable realistic physical models and advance discovery. Author summary3D imaging of cellular components and associated reconstruction methods have made great strides in the past decade, opening windows into the complex intraceullar organization. These advances also mean that computational tools need to be developed to work with these images not just for purposes of visualization but also for biophysical simulations. Here, we describe a pipeline that takes images from electron microscopy as input and produces smooth surface and volume meshes as output. These meshes are suitable for building high-quality finite element simulations of cellular processes modeled by ordinary and partial differential equations, bringing us closer to realizing the goal of generating high-resolution simulations of such phenomena in realistic geometries. We demonstrate the utility of this pipeline by meshing 3D reconstructions of dendritic spines, calculating 1 the curvatures of the different component membranes, and conducting finite-element simulations of reaction-diffusion equations using the generated meshes. The software tools employed in our pipeline are community driven, open source, and free. We believe that technologies such as those presented will enable a new frontier in biophysical simulations in realistic geometries.