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      V3D enables real-time 3D visualization and quantitative analysis of large-scale biological image data sets

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          Abstract

          The V3D system provides three-dimensional (3D) visualization of gigabyte-sized microscopy image stacks in real time on current laptops and desktops. Combined with highly ergonomic features for selecting an X, Y, Z location of an image directly in 3D space and for visualizing overlays of a variety of surface objects, V3D streamlines the on-line analysis, measurement, and proofreading of complicated image patterns. V3D is cross-platform and can be enhanced by plug-ins. We built V3D-Neuron on top of V3D to reconstruct complex 3D neuronal structures from large brain images. V3D-Neuron enables us to precisely digitize the morphology of a single neuron in a fruit fly brain in minutes, with about 17-fold improvement in reliability and 10-fold savings in time compared to other neuron reconstruction tools. Using V3D-Neuron, we demonstrated the feasibility of building a 3D digital atlas of neurite tracts in the fruit fly brain.

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          New techniques for imaging, digitization and analysis of three-dimensional neural morphology on multiple scales.

          S. L. Wearne, A. Rodríguez, D Ehlenberger … (2005)
          Cognitive impairment in normal aging and neurodegenerative diseases is accompanied by altered morphologies on multiple scales. Understanding of the role of these structural changes in producing functional deficits in brain aging and neuropsychiatric disorders requires accurate three-dimensional representations of neuronal morphology, and realistic biophysical modeling that can directly relate structural changes to altered neuronal firing patterns. To date however, tools capable of resolving, digitizing and analyzing neuronal morphology on both local and global scales, and with sufficient throughput and automation, have been lacking. The precision of existing image analysis-based morphometric tools is restricted at the finest scales, where resolution of fine dendritic features and spine geometry is limited by the skeletonization methods used, and by quantization errors arising from insufficient imaging resolution. We are developing techniques for imaging, reconstruction and analysis of neuronal morphology that capture both local and global structural variation. To minimize quantization error and evaluate more precisely the fine geometry of dendrites and spines, we introduce a new shape analysis technique, the Rayburst sampling algorithm that uses the original grayscale data rather than the segmented images for precise, continuous radius estimation, and multidirectional radius sampling to represent non-circular branch cross-sections and anisotropic structures such as dendritic spine heads, with greater accuracy. We apply the Rayburst technique to 3D neuronal shape analysis at different scales. We reconstruct and digitize entire neurons from stacks of laser-scanning microscopy images, as well as globally complex structures such as multineuron networks and microvascular networks. We also introduce imaging techniques necessary to recover detailed information on three-dimensional mass distribution and surface roughness of amyloid beta plaques from human Alzheimer's disease patients and from the Tg2576 mouse that expresses the "Swedish" mutation of the amyloid precursor protein. By providing true three-dimensional morphometry of complex histologic structures on multiple scales, the tools described in this report will enable multiscale biophysical modeling studies capable of testing potential mechanisms by which altered dendritic structure, spine geometry and network branching patterns that occur in normal aging and in many brain disorders, determine deficits of functions such as working memory and cognition.
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            Bioimage informatics: a new area of engineering biology

            Hanchuan Peng (2008)
            In recent years, the deluge of complicated molecular and cellular microscopic images creates compelling challenges for the image computing community. There has been an increasing focus on developing novel image processing, data mining, database and visualization techniques to extract, compare, search and manage the biological knowledge in these data-intensive problems. This emerging new area of bioinformatics can be called ‘bioimage informatics’. This article reviews the advances of this field from several aspects, including applications, key techniques, available tools and resources. Application examples such as high-throughput/high-content phenotyping and atlas building for model organisms demonstrate the importance of bioimage informatics. The essential techniques to the success of these applications, such as bioimage feature identification, segmentation and tracking, registration, annotation, mining, image data management and visualization, are further summarized, along with a brief overview of the available bioimage databases, analysis tools and other resources. Contact: pengh@janelia.hhmi.org Supplementary information: Supplementary data are available at Bioinformatics online.
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              Advances in light microscopy for neuroscience.

              Arun K. Ghosh, Brian Wilt, E Ho … (2008)
              Since the work of Golgi and Cajal, light microscopy has remained a key tool for neuroscientists to observe cellular properties. Ongoing advances have enabled new experimental capabilities using light to inspect the nervous system across multiple spatial scales, including ultrastructural scales finer than the optical diffraction limit. Other progress permits functional imaging at faster speeds, at greater depths in brain tissue, and over larger tissue volumes than previously possible. Portable, miniaturized fluorescence microscopes now allow brain imaging in freely behaving mice. Complementary progress on animal preparations has enabled imaging in head-restrained behaving animals, as well as time-lapse microscopy studies in the brains of live subjects. Mouse genetic approaches permit mosaic and inducible fluorescence-labeling strategies, whereas intrinsic contrast mechanisms allow in vivo imaging of animals and humans without use of exogenous markers. This review surveys such advances and highlights emerging capabilities of particular interest to neuroscientists.
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                Author and article information

                Journal
                Journal ID (nlm-journal-id): 9604648
                Journal ID (pubmed-jr-id): 20305
                Journal ID (nlm-ta): Nat Biotechnol
                Title: Nature biotechnology
                ISSN (Print): 1087-0156
                ISSN (Electronic): 1546-1696
                Publication date Nihms-submitted: 12 March 2010
                Publication date (Electronic): 14 March 2010
                Publication date (Print): April 2010
                Publication date PMC-release: 1 October 2010
                Volume: 28
                Issue: 4
                Pages: 348-353
                Affiliations
                Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA, 20147, USA
                Author notes
                [* ]Corresponding author ( pengh@ 123456janelia.hhmi.org )
                Article
                Manuscript ID: hhmipa177792
                DOI: 10.1038/nbt.1612
                PMC ID: 2857929
                PubMed ID: 20231818
                SO-VID: 1f722b7a-5082-4e09-b85e-ace02cc9f7ec
                License:

                Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

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                Funding
                Funded by: Howard Hughes Medical Institute
                Award ID: ||HHMI_
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                Subject: Article

                ScienceOpen disciplines: Biotechnology
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                ScienceOpen disciplines: Biotechnology

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