Three‐dimensional immersive virtual reality for studying cellular compartments in 3D models from EM preparations of neural tissues

Advances in the application of electron microscopy (EM) to serial imaging are opening doors to new ways of analyzing cellular structure. New and improved algorithms and workflows for manual and semiautomated segmentation allow us to observe the spatial arrangement of the smallest cellular features with unprecedented detail in full three‐dimensions. From larger samples, higher complexity models can be generated; however, they pose new challenges to data management and analysis. Here we review some currently available solutions and present our approach in detail. We use the fully immersive virtual reality (VR) environment CAVE (cave automatic virtual environment), a room in which we are able to project a cellular reconstruction and visualize in 3D, to step into a world created with Blender, a free, fully customizable 3D modeling software with NeuroMorph plug‐ins for visualization and analysis of EM preparations of brain tissue. Our workflow allows for full and fast reconstructions of volumes of brain neuropil using ilastik, a software tool for semiautomated segmentation of EM stacks. With this visualization environment, we can walk into the model containing neuronal and astrocytic processes to study the spatial distribution of glycogen granules, a major energy source that is selectively stored in astrocytes. The use of CAVE was key to the observation of a nonrandom distribution of glycogen, and led us to develop tools to quantitatively analyze glycogen clustering and proximity to other subcellular features. J. Comp. Neurol. 524:23–38, 2016. © 2015 Wiley Periodicals, Inc.     

Contour-propagation algorithms for semi-automated reconstruction of neural processes

A new technique, "serial block face scanning electron microscopy" (SBFSEM), allows for automatic sectioning and imaging of biological tissue with a scanning electron microscope. Image stacks generated with this technology have a resolution sufficient to distinguish different cellular compartments, including synaptic structures, which should make it possible to obtain detailed anatomical knowledge of complete neuronal circuits. Such an image stack contains several thousands of images and is recorded with a minimal voxel size of 10-20 nm in the x- and y-direction and 30 nm in z-direction. Consequently, a tissue block of 1 mm(3)(the approximate volume of the Calliphora vicina brain) will produce several hundred terabytes of data. Therefore, highly automated 3D reconstruction algorithms are needed. As a first step in this direction we have developed semi-automated segmentation algorithms for a precise contour tracing of cell membranes. These algorithms were embedded into an easy-to-operate user interface, which allows direct 3D observation of the extracted objects during the segmentation of image stacks. Compared to purely manual tracing, processing time is greatly accelerated.     

Micro3D: computer program for three-dimensional reconstruction visualization, and analysis of neuronal populations and barin regions

This article presents a computer program, Micro3D, designed for 3-D reconstruction, visualization, and analysis of coordinate-data (points and lines) recorded from serial sections. The software has primarily been used for studying shapes and dimension of brain regions (contour line data) and distributions of cellular elements such as neuronal cell bodies or axonal terminal fields labeled with tract-tracing techniques (point data). The tissue elements recorded could equally well be labeled with use of other techniques, the only requirement being that the data collected are saved as x,y,z coordinates. Data are typically imported from image-combining computerized microscopy systems or image analysis systems, such as Neurolucida (MicroBrightField, Colchester, VT) or analySIS (Soft Imaging System, Gmbh, Münster, Germany). System requirements are a PC running LINUX. Reconstructions in Micro3D may be rotated and zoomed in real-time, and submitted to perspective viewing and stereo-imaging. Surfaces are re-synthesized on the basis of stacks of contour lines. Clipping is used for defining section-independent subdivisions of the reconstruction. Flattening of curved sheets of points layers (e.g., neurons in a layer) facilitates inspection of complicated distribution patterns. Micro3D computes color-coded density maps. Opportunities for translation of data from different reconstructions into common coordinate systems are also provided. This article demonstrates the use of Micro3D for visualization of complex neuronal distribution patterns in somatosensory and auditory systems. The software is available for download on conditions posted at the NeSys home pages (http://www.nesys.uio.no/) and at The Rodent Brain Workbench (http://www.rbwb.org/).     

The problem of the morphological noise in reconstructed dendritic arborizations

For technical, instrumental and operator-related reasons, three-dimensional (3D) reconstructions of neurons obtained from intracellularly stained neuronal pieces scattered in serial sections are blurred by some morphological noise. This noise may strongly invalidate conclusions drawn from models built using the 3D reconstructions and it must be taken into account when retrieving digitized neurons from available databases. We analyse on several vertebrate neurons examples the main noise-generating sources and the consequences of the noise on the 'quality' of the data. We show how the noise can be detected and evaluated in any database, if sufficient information is presented in this database.     

Automation of 3D reconstruction of neural tissue from large volume of conventional serial section transmission electron micrographs

We describe an approach for automation of the process of reconstruction of neural tissue from serial section transmission electron micrographs. Such reconstructions require 3D segmentation of individual neuronal processes (axons and dendrites) performed in densely packed neuropil. We first detect neuronal cell profiles in each image in a stack of serial micrographs with multi-scale ridge detector. Short breaks in detected boundaries are interpolated using anisotropic contour completion formulated in fuzzy-logic framework. Detected profiles from adjacent sections are linked together based on cues such as shape similarity and image texture. Thus obtained 3D segmentation is validated by human operators in computer-guided proofreading process. Our approach makes possible reconstructions of neural tissue at final rate of about 5 microm3/manh, as determined primarily by the speed of proofreading. To date we have applied this approach to reconstruct few blocks of neural tissue from different regions of rat brain totaling over 1000microm3, and used these to evaluate reconstruction speed, quality, error rates, and presence of ambiguous locations in neuropil ssTEM imaging data.     

Optical clearing improves the imaging depth and signal‐to‐noise ratio for digital analysis and three‐dimensional projection of the human enteric nervous system

Background Due to the dispersed nature of neurites and fibers, the microtome‐based 2‐dimensional histology provides only a limited perspective of the enteric nervous system. To visualize the enteric plexus, we applied optical clearing to avoid scattering in the human ileum to facilitate photon penetration for 3‐dimensional (3‐D) microscopy of the neural tissue. Methods Human ileal specimens were derived by trimming the donor bowel due to its excess length during the clinical trial of small intestinal transplantation. The pan‐neuronal marker PGP9.5 was used as the immunostaining target to reveal the enteric plexuses. The labeled tissues were immersed in the optical‐clearing solution prior to deep‐tissue confocal microscopy. The serial sections were digitally analyzed and processed by reconstruction algorithms for 3‐D visualization. Key Results Optical clearing of the ileal specimen led to less fluorescence signal decay along the focal path in the tissue and a higher signal‐to‐noise ratio of the confocal micrographs in comparison with the untreated saline control. Taking advantage of the high signal‐to‐noise ratio images, we applied software‐based signal analysis to identify the presence of the nerve fibers and quantify the signal peaks. The image stacks derived from the serial anatomic micrographs created panoramic views of the gut wall innervations with their associated microstructures. Conclusions & Inferences We provide an optical approach to improve the imaging depth in 3‐D neurohistology of the human ileum. This methodology has significant promise in facilitating our understanding of the enteric nervous system in health and disease.     

Montage: a system for three-dimensional reconstruction by personal computer

This paper describes a simplified system for serial section three-dimensional (3-D) reconstruction. A set of 9 software programs runs on a standard personal computer and produces camera-ready illustrations suitable for publication. The user enters trace points on a digitizing tablet from sections that have been already aligned. A 3-D view of the reconstructed object is generated which can be displayed with hidden lines removed. Analysis of volume, surface area and autoradiographic grain density are performed automatically. A relational database query language allows display and analysis of a selected subset of the data. The system runs under the UNIX operating system which allows the programs to be easily transported to new hardware or modified for other purposes.     

Three-dimensional reconstruction of human spinal cord based on histological serial sections

BACKGROUND:It is not possible to reconstruct the inner structure of the spinal cord.such as gray matter and spinal tracts,from the Visual Human Project database or CT and MRI databases,due to low image resolution and contrast in macrosection images.OBJECTIVE:To explore a semi-automatic computerized three-dimensional(3D)reconstruction of human spinal cord based on histological serial sections,in order to solve issues such as low contrast.DESIGN,TIME AND SETTING:An experimental study combining serial section techniques and 3D reconstruction,performed in the laboratory of Hunlan Anatomy and Histoembryology at the Medical School of Nantong University during January to April 2008.SETTING:Department of Anatomy,Institute of Neurobiology,Jiangsu Province Key Laboratory of Neural Regeneration,Laboratory of Image Engineering.MATERIALS:A human lumbar spinal cord segment from fresh autopsy material of an adult male.M[ETHODS:After 4% paraformaldehyde fixation for three days,serial sections of the lumbar spinal cord were cut on a Leica cryostat and mounted on slides in sequence,with eight sections aligned separately on each slide.All sections were stained with Luxol Fast Blue to reveal myelin sheaths.After gradient dehydration and clearing,the stained slides were coverslipped.Sections were observed and images recorded under a light microscope using a digital camera.Six images were acquired at ×25 magnification and automatically stitched into a complete section image.Aftel-all serial images were obtained,96 complete serial images of the human lumbar cord segment were automatically processed with "Curves","Autocontrast","Gray scale 8 bit","Invert","Image resize to 50%"steps using Photoshop 7.0 software.All images were added in order into 3D-DOCTOR 4.0 software as a stack where serial images were automatically realigned with neighbonng images and semi-automatically segmented for white matter and gray matter.Finally,simple surface and volume reconstruction were completed on a personal computer.The reconstructed human lumbar spinal cord segment was interactively observed,cut.and measured.MAIN OUTCOME MEASURES:The reconstructed human lumbar spinal cord segment.RESULTS:Compared with serial images obtained from other image modalities,such as CT,MRI,and macrosections from The Visual Human Project database.the Luxol Fast Blue stained histological serial section images exhibited higher resolution and contrast between gray and white matter.Image processing and 3D reconstruction steps were semi-automatically performed with related software.The 3D reconstructed human lumbar cord segment were observed,cut,and measured on a PC.CONCLUSION:A semi-automatically computerized method,based on histological serial sections,is an effective way to 3D-reconstruct the human spinal cord.     

Three-dimensional reconstruction of human spinal cord based on histological serial sections**☆

BACKGROUND： It is not possible to reconstruct the inner structure of the spinal cord, such as gray matter and spinal tracts, from the Visual Human Project database or CT and MRI databases, due to low image resolution and contrast in macrosection images.
OBJECTIVE： To explore a semi-automatic computerized three-dimensional （3D） reconstruction of human spinal cord based on histological serial sections, in order to solve issues such as low contrast.
DESIGN, TIME AND SETTING： An experimental study combining serial section techniques and 3D reconstruction, performed in the laboratory of Human Anatomy and Histoembryology at the Medical School of Nantong University during January to April 2008.
SETTING： Department of Anatomy, Institute of Neurobiology, Jiangsu Province Key Laboratory of Neural Regeneration, Laboratory of Image Engineering.
MATERIALS： A human lumbar spinal cord segment from fresh autopsy material of an adult male.
METHODS： After 4% paraformaldehyde fixation for three days, serial sections of the lumbar spinal cord were cut on a Leica cryostat and mounted on slides in sequence, with eight sections aligned separately on each slide. All sections were stained with Luxol Fast Blue to reveal myelin sheaths. After gradient dehydration and clearing, the stained slides were coverslipped. Sections were observed and images recorded under a light microscope using a digital camera. Six images were acquired at x25 magnification and automatically stitched into a complete section image. After all serial images were obtained, 96 complete serial images of the human lumbar cord segment were automatically processed with ＂Curves＂, ＂Autocontrast＂, ＂Gray scale 8 bit＂, ＂Invert＂, ＂Image resize to 50%＂ steps using Photoshop 7.0 software. All images were added in order into 3D-DOCTOR 4.0 software as a stack, where serial images were automatically realigned with neighboring images and semi-automatically segmented for white matter and gray matter. Finally, simple surface and volume recon     

Objective image alignment for three-dimensional reconstruction of digital autoradiograms

Autoradiography can generate large quantities of information related to brain metabolism, blood flow, transport across the blood-brain barrier, neurotransmitter-receptor binding and other aspects of brain function. Three-dimensional (3D) reconstruction of digitized autoradiograms provides a mechanism for efficient analysis of function, in detail, over the entire brain. 3D reconstructions of the mean and variance can be obtained by superimposing data from similar experiments, leading ultimately to 3D reconstructions of differences with statistical tests of significance. Image registration is essential for reconstruction, and this article reports two independent algorithms for coronal image alignment that have been successfully implemented in computer programs. The first algorithm superimposes the centroids and principal axes of serial images; the extent and direction of the translation and rotation required for each image is obtained from an analysis of the inertia matrix of that image. The second algorithm matches the edges of structure features in serial-adjacent images, from analyses of the cross-correlation function of each pair of adjacent images. The cross-correlation method requires a great deal more computation than the principal axes method, but it can align damaged sections not reliably treated by the principal axes method. The methods are described in detail, and a quantitative assessment of the registration of non-identical images is considered.     

Three-dimensional reconstruction: a tissue embedding method for alignment of serial sections

Three-dimensional (3D) reconstruction from serial sections that are undistorted and true-to-life is only possible when a reference system exists that allows correct matching of the section drawings. This paper describes a simple method for producing reference lines that ensures proper alignment of the drawings. (1) The specimen is embedded in a rectangular form, (2) the sides of the block are painted, and (3) the embedded specimen is sectioned exactly perpendicular to the painted sides of the block. Thus, in each section the paint appears as dark lines which serve as reference lines for matching the sections.     

基于轮廓拼接算法三维重建中国数字人肩部骨骼肌肉结构

针对中国数字人的断面切片图像,建立肩部骨骼肌肉包括皮肤的三维模型。按照图像数据集的获取与配准、预处理、三维重构的流程。采用基于拐点的精度可调的轮廓拼接三维重构算法,通过轮廓比对找出相对正确的匹配关系,对中国数字人肩部结构进行三维重建和几何保存。结果获得了肩部骨骼和肌肉包括皮肤的结构的重建,并可以进行任意角度观察,可以调整任意某结构的透明度,清楚显示肩部骨骼肌肉等三维位置关系。结果提示,基于轮廓拼接算法的三维模型在结构上与原真实标本误差小,为进一步的人体个体化研究奠定了基础。     

3D volume reconstruction of a mouse brain from histological sections using warp filtering

Sectioning tissues for optical microscopy often introduces upon the resulting sections distortions that make 3D reconstruction difficult. Here we present an automatic method for producing a smooth 3D volume from distorted 2D sections in the absence of any undistorted references. The method is based on pairwise elastic image warps between successive tissue sections, which can be computed by 2D image registration. Using a Gaussian filter, an average warp is computed for each section from the pairwise warps in a group of its neighboring sections. The average warps deform each section to match its neighboring sections, thus creating a smooth volume where corresponding features on successive sections lie close to each other. The proposed method can be used with any existing 2D image registration method for 3D reconstruction. In particular, we present a novel image warping algorithm based on dynamic programming that extends Dynamic Time Warping in 1D speech recognition to compute pairwise warps between high-resolution 2D images. The warping algorithm efficiently computes a restricted class of 2D local deformations that are characteristic between successive tissue sections. Finally, a validation framework is proposed and applied to evaluate the quality of reconstruction using both real sections and a synthetic volume.     

Three-dimensional reconstruction of tissue using computer-generated images

In the study of brain ventricles for both teaching and research, it is often of considerable advantage to graphically display the reconstructed shape of the specimen. This paper describes the making of two-dimensional serial cross-sections and their storage for subsequent manipulation and display on a personal computer; the three-dimensional (3D) reconstructions may have hidden lines removed and various parts coloured for definition of areas of interest, for example the density and position of pyknotic (dead) nuclei. Current research involved the investigation of the effects of maternal hyperthermia on early embryonic brains. The 3D reconstructions were found ideal for understanding the temporal changes occurring in embryonic brains subjected to defined maternal heat stresses. The method involved 4 X 4 matrices using homogenous coordinate theory, being the most ideal and allowing a constant mechanism for all transformations. Total time from examination of sections to obtaining an accurate printed 3D reconstruction is approximately 1 h if 22 sections are used.     

Mapping the avian visual tectofugal pathway using 3D reconstruction

Image processing in amniotes is usually accomplished by the thalamofugal and/or tectofugal visual systems. In laterally eyed birds, the tectofugal system dominates with functions such as color and motion processing, spatial orientation, stimulus identification, and localization. This makes it a critical system for complex avian behavior. Here, the brains of chicks, Gallus gallus, were used to produce serial brain sections in either coronal, sagittal, or horizontal planes and stained with either Nissl and Gallyas silver myelin or Luxol fast blue stain and cresyl echt violet (CEV). The emerging techniques of diffusible iodine-based contrast-enhanced computed tomography (diceCT) coupled with serial histochemistry in three planes were used to generate a comprehensive three-dimensional (3D) model of the avian tectofugal visual system. This enabled the 3D reconstruction of tectofugal circuits, including the three primary neuronal projections. Specifically, major components of the system included four regions of the retina, layers of the optic tectum, subdivisions of the nucleus rotundus in the thalamus, the entopallium in the forebrain, and supplementary components connecting into or out of this major avian visual sensory system. The resulting 3D model enabled a better understanding of the structural components and connectivity of this complex system by providing a complete spatial organization that occupied several distinct brain regions. We demonstrate how pairing diceCT with traditional histochemistry is an effective means to improve the understanding of, and thereby should generate insights into, anatomical and functional properties of complicated neural pathways, and we recommend this approach to clarify enigmatic properties of these pathways.     

Common Atlas Format and 3D Brain Atlas Reconstructor: Infrastructure for Constructing 3D Brain Atlases

One of the challenges of modern neuroscience is integrating voluminous data of diferent modalities derived from a variety of specimens. This task requires a common spatial framework that can be provided by brain atlases. The first atlases were limited to two-dimentional presentation of structural data. Recently, attempts at creating 3D atlases have been made to offer navigation within non-standard anatomical planes and improve capability of localization of different types of data within the brain volume. The 3D atlases available so far have been created using frameworks which make it difficult for other researchers to replicate the results. To facilitate reproducible research and data sharing in the field we propose an SVG-based Common Atlas Format (CAF) to store 2D atlas delineations or other compatible data and 3D Brain Atlas Reconstructor (3dBAR), software dedicated to automated reconstruction of three-dimensional brain structures from 2D atlas data. The basic functionality is provided by (1) a set of parsers which translate various atlases from a number of formats into the CAF, and (2) a module generating 3D models from CAF datasets. The whole reconstruction process is reproducible and can easily be configured, tracked and reviewed, which facilitates fixing errors. Manual corrections can be made when automatic reconstruction is not sufficient. The software was designed to simplify interoperability with other neuroinformatics tools by using open file formats. The content can easily be exchanged at any stage of data processing. The framework allows for the addition of new public or proprietary content.     

Two useful techniques in three-dimensional electron microscopy: quarter-micron serial sectioning and stereoscopy

Quarter-micron serial sectioning is a technique useful for 3-D analyses in which light microscopical resolution is not sufficient and the maximal resolution of the electron microscope is not necessary. We propose that the technique described here is advantageous for many current electron microscopic studies in which ultrathin sections are commonly used. In particular, the sections are sturdier; they yield high-contrast images; they contain, per section, more information about the third dimension, information that can be retrieved through stereoscopy; and, when it comes to 3-D reconstruction from serial sections, less sections are needed to reconstruct tissue elements contained in a bloc of a given size. Compared to thicker sections, quarter-micron sections yield images of acceptable readability.     

A method for the automatic segmentation of autoradiographic image stacks and spatial normalization of functional cortical activity patterns

This paper introduces two new methods for the automatic anatomical and functional analysis of neurobiological autoradiographic image stacks, such as 2-fluoro-deoxyglucose (2FDG) images. The difficulty in the evaluation of these "2(1/2)D" datasets is that they do not inherently represent a continuous 3D data volume (as generated by MRI or CT), but consist of a stack of images from single tissue slices, suffering from unavoidable preparation artifacts. In the first part of the paper, a semi-automatic segmentation method is presented which generates a 3D surface model of certain brain structures and which is robust against different cutting directions with respect to the brain coordinate system. The method saves man-hours compared to manual segmentation and the results are highly reproducible. In the second part, a fully automatic method for the extraction, analysis and 3D visualization of functional information is described, which allows not only a more accurate localization of activation sites, but also greatly enhances the comparability of different individuals. Results are shown for 2FDG autoradiographs from rat brains under acoustical stimulation.     

An inexpensive microcomputer-based image-analysis system: novel applications to quantitative autoradiography

We describe a relatively inexpensive, yet versatile and powerful microcomputer-based image-analysis system, and its applications to processing of deoxyglucose autoradiographic data. Images are acquired via a video camera mounted on a light microscope or a light box, and digitized in 40 ms to 512 X 512 picture elements with 8-bit resolution (256 gray levels). The bit-mapped image analysis hardware can provide up to 256 colors for pseudo-color coding, and virtually instantaneous readout of brightness values for densitometry. The system is controlled by an 8-bit S-100 bus microcomputer, providing flexibility and ease of expansion. In addition to pseudo-color coding and densitometry, we have developed programs for averaging of successive sections, image subtraction and quantitative reconstruction of different planes of section from serial autoradiograms.     

High resolution scanning and three-dimensional reconstruction of cellular events in large objects during brain development.

Detailed knowledge of the spatial and temporal interactions of distinct cellular events and of the genes involved in their regulation is a precondition for the understanding of morphogenetic and pathogenetic processes. Here, how patterns of cellular events in large objects can be visualized with the help of the image acquisition system 'Huge Image' is demonstrated. Huge images are composed of a multitude of small images scanned with the highest light microscopical resolution. The system is equipped with a programmable autofocus device and permits precise and rapid cytological diagnosis. A vector-based three-dimensional (3-D) reconstruction method which, in future projects, will be combined with 'Huge Image', is applied to visualize dynamic interactions between macrophages and the occurrence of apoptotic neuroepithelial cells in the early developing forebrain of Tupaia belangeri (Scandentia). Proportionally correct meshwire surfaces of small and large objects are generated independently of each other. The combined reconstruction of cellular events and large embryonic surfaces can be carried out from only subsets of histological serial sections, and, compared with volume-based systems, with a much lower need for memory. The practicability of our approach is compared with recent other methods used to demonstrate apoptotic patterns.