Post-acquisition image based compensation for thickness variation in microscopy section series

Serial section Microscopy is an established method for volumetric anatomy reconstruction. Section series imaged with Electron Microscopy are currently vital for the reconstruction of the synaptic connectivity of entire animal brains such as that of Drosophila melanogaster. The process of removing ultrathin layers from a solid block containing the specimen, however, is a fragile procedure and has limited precision with respect to section thickness. We have developed a method to estimate the relative z-position of each individual section as a function of signal change across the section series. First experiments show promising results on both serial section Transmission Electron Microscopy (ssTEM) data and Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) series. We made our solution available as Open Source plugins for the TrakEM2 software and the ImageJ distribution Fiji

3D mesh processing using GAMer 2 to enable reaction-diffusion simulations in realistic cellular geometries

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.Comment: 39 pages, 14 figures. High resolution figures and supplemental movies available upon reques

Parameter-Free Binarization and Skeletonization of Fiber Networks from Confocal Image Stacks

We present a method to reconstruct a disordered network of thin biopolymers, such as collagen gels, from three-dimensional (3D) image stacks recorded with a confocal microscope. The method is based on a template matching algorithm that simultaneously performs a binarization and skeletonization of the network. The size and intensity pattern of the template is automatically adapted to the input data so that the method is scale invariant and generic. Furthermore, the template matching threshold is iteratively optimized to ensure that the final skeletonized network obeys a universal property of voxelized random line networks, namely, solid-phase voxels have most likely three solid-phase neighbors in a neighborhood. This optimization criterion makes our method free of user-defined parameters and the output exceptionally robust against imaging noise

4D imaging of heart vaso-architecture after myocardial infarction

Cardiovascular diseases remain the number one cause of death globally. There is an ongoing desire to study the distribution and structural changes of the vaso-architecture in the diseased heart in cardiovascular research groups all over the world. The ability to acquire high resolution 3D-images of the heart vasculature enables to study heart diseases more in detail and eventually obtain interesting new findings and new treatments. In this work, we introduce a pipeline for high resolution 3D-imaging of the changes in mouse heart vasculature after a myocardial infarction is produced with Single Plane Illumination Microscopy (SPIM). To achieve high resolution 3D-images, protocols for optical tissue clearing (CUBIC tissue clearing technique) were combined with vasculature labelling methods (IHC and intravenous perfused lectin), enabling the visualization for the very first time of the whole heart vasculature. We here also describe the methods used for image pre-processing of the acquired data, mainly for correction of SPIM-image artifacts and for segmentation of the structures of interest. Finally, the analysis of the changes in vasculature between healthy hearts with the different stages of chronic myocardial infarction (7, 14 and 28 days post-infarction) will provide us a tool to know how this disease affects not only to infarcted region but to the whole heart volume.Ingeniería Biomédic