Scalable electron tomography for connectomics.

We demonstrate limited-tilt, serial section electron tomography (ET), which can non-destructively map brain circuits over large 3D volumes and reveal high-resolution, supramolecular details within subvolumes of interest. We show accelerated ET imaging of thick sections (>500 nm) with the capacity to resolve key features of neuronal circuits including chemical synapses, endocytic structures, and gap junctions. Furthermore, we systematically assessed how imaging parameters affect image quality and speed to enable connectomic-scale projects.

Elemental mapping of labelled biological specimens at intermediate energy loss in an energy-filtered TEM acquired using a direct detection device.

The technique of colour EM that was recently developed enabled localisation of specific macromolecules/proteins of interest by the targeted deposition of diaminobenzidine (DAB) conjugated to lanthanide chelates. By acquiring lanthanide elemental maps by energy-filtered transmission electron microscopy (EFTEM) and overlaying them in pseudo-colour over the conventional greyscale TEM image, a colour EM image is generated. This provides a powerful tool for visualising subcellular component/s, by the ability to clearly distinguish them from the general staining of the endogenous cellular material.

CDeep3M-Plug-and-Play cloud-based deep learning for image segmentation.

As biomedical imaging datasets expand, deep neural networks are considered vital for image processing, yet community access is still limited by setting up complex computational environments and availability of high-performance computing resources. We address these bottlenecks with CDeep3M, a ready-to-use image segmentation solution employing a cloud-based deep convolutional neural network. We benchmark CDeep3M on large and complex two-dimensional and three-dimensional imaging datasets from light, X-ray, and electron microscopy.

Probability Map Viewer: near real-time probability map generator of serial block electron microscopy collections.

Summary: To expedite the review of semi-automated probability maps of organelles and other features from 3D electron microscopy data we have developed Probability Map Viewer, a Java-based web application that enables the computation and visualization of probability map generation results in near real-time as the data are being collected from the microscope. Probability Map Viewer allows the user to select one or more voxel classifiers, apply them on a sub-region of an active collection, and visualize the results as overlays on the raw data via any web browser using a personal computer or mobile device. Thus, Probability Map Viewer accelerates and informs the image analysis workflow by providing a tool for experimenting with and optimizing dataset-specific segmentation strategies during imaging.

Deceleration of probe beam by stage bias potential improves resolution of serial block-face scanning electron microscopic images.

Serial block-face scanning electron microscopy (SBEM) is quickly becoming an important imaging tool to explore three-dimensional biological structure across spatial scales. At probe-beam-electron energies of 2.0 keV or lower, the axial resolution should improve, because there is less primary electron penetration into the block face.

X-ray microscopy as an approach to increasing accuracy and efficiency of serial block-face imaging for correlated light and electron microscopy of biological specimens.

The recently developed three-dimensional electron microscopic (EM) method of serial block-face scanning electron microscopy (SBEM) has rapidly established itself as a powerful imaging approach. Volume EM imaging with this scanning electron microscopy (SEM) method requires intense staining of biological specimens with heavy metals to allow sufficient back-scatter electron signal and also to render specimens sufficiently conductive to control charging artifacts. These more extreme heavy metal staining protocols render specimens light opaque and make it much more difficult to track and identify regions of interest (ROIs) for the SBEM imaging process than for a typical thin section transmission electron microscopy correlative light and electron microscopy study.

Improving signal to noise in labeled biological specimens using energy-filtered TEM of sections with a drift correction strategy and a direct detection device.

Energy filtered transmission electron microscopy techniques are regularly used to build elemental maps of spatially distributed nanoparticles in materials and biological specimens. When working with thick biological sections, electron energy loss spectroscopy techniques involving core-loss electrons often require exposures exceeding several minutes to provide sufficient signal to noise. Image quality with these long exposures is often compromised by specimen drift, which results in blurring and reduced resolution.

Scientific Grid activities and PKI deployment in the Cybermedia Center, Osaka University.

The Cybermedia Center (CMC), Osaka University, is a research institution that offers knowledge and technology resources obtained from advanced researches in the areas of large-scale computation, information and communication, multimedia content and education. Currently, CMC is involved in Japanese national Grid projects such as JGN II (Japan Gigabit Network), NAREGI and BioGrid. Not limited to Japan, CMC also actively takes part in international activities such as PRAGMA.

Biomedical informatics research network: building a national collaboratory to hasten the derivation of new understanding and treatment of disease.

Through support from the National Institutes of Health's National Center for Research Resources, the Biomedical Informatics Research Network (BIRN) is pioneering the use of advanced cyberinfrastructure for medical research. By synchronizing developments in advanced wide area networking, distributed computing, distributed database federation, and other emerging capabilities of e-science, the BIRN has created a collaborative environment that is paving the way for biomedical research and clinical information management. The BIRN Coordinating Center (BIRN-CC) is orchestrating the development and deployment of key infrastructure components for immediate and long-range support of biomedical and clinical research being pursued by domain scientists in three neuroimaging test beds.