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Three-dimensional reconstruction of serial mouse brain sections: solution for flattening high-resolution large-scale mosaics.

Frontiers in neuroanatomy | 2011

Recent advances in high-throughput technology facilitate massive data collection and sharing, enabling neuroscientists to explore the brain across a large range of spatial scales. One such form of high-throughput data collection is the construction of large-scale mosaic volumes using light microscopy (Chow et al., 2006; Price et al., 2006). With this technology, researchers can collect and analyze high-resolution digitized volumes of whole brain sections down to 0.2 μm. However, until recently, scientists lacked the tools to easily handle these large high-resolution datasets. Furthermore, artifacts resulting from specimen preparation limited volume reconstruction using this technique to only a single tissue section. In this paper, we carefully describe the steps we used to digitally reconstruct a series of consecutive mouse brain sections labeled with three stains, a stain for blood vessels (DiI), a nuclear stain (TO-PRO-3), and a myelin stain (FluoroMyelin). These stains label important neuroanatomical landmarks that are used for stacking the serial sections during reconstruction. In addition, we show that the use of two software applications, ir-Tweak and Mogrifier, in conjunction with a volume flattening procedure enable scientists to adeptly work with digitized volumes despite tears and thickness variations within tissue sections. These applications make processing large-scale brain mosaics more efficient. When used in combination with new database resources, these brain maps should allow researchers to extend the lifetime of their specimens indefinitely by preserving them in digital form, making them available for future analyses as our knowledge in the field of neuroscience continues to expand.

Pubmed ID: 21629828 RIS Download

Research resources used in this publication

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Antibodies used in this publication

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Associated grants

  • Agency: NCRR NIH HHS, United States
    Id: P41 RR004050
  • Agency: NIBIB NIH HHS, United States
    Id: R01 EB005832
  • Agency: NIDA NIH HHS, United States
    Id: R25 DA026401

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Cell Centered Database (tool)

RRID:SCR_002168

THIS RESOURCE IS NO LONGER IN SERVICE, documented June 5, 2017. It has been merged with Cell Image Library. Database for sharing and mining cellular and subcellular high resolution 2D, 3D and 4D data from light and electron microscopy, including correlated imaging that makes unique and valuable datasets available to the scientific community for visualization, reuse and reanalysis. Techniques range from wide field mosaics taken with multiphoton microscopy to 3D reconstructions of cellular ultrastructure using electron tomography. Contributions from the community are welcome. The CCDB was designed around the process of reconstruction from 2D micrographs, capturing key steps in the process from experiment to analysis. The CCDB refers to the set of images taken from microscope the as the Microscopy Product. The microscopy product refers to a set of related 2D images taken by light (epifluorescence, transmitted light, confocal or multiphoton) or electron microscopy (conventional or high voltage transmission electron microscopy). These image sets may comprise a tilt series, optical section series, through focus series, serial sections, mosaics, time series or a set of survey sections taken in a single microscopy session that are not related in any systematic way. A given set of data may be more than one product, for example, it is possible for a set of images to be both a mosaic and a tilt series. The Microscopy Product ID serves as the accession number for the CCDB. All microscopy products must belong to a project and be stored along with key specimen preparation details. Each project receives a unique Project ID that groups together related microscopy products. Many of the datasets come from published literature, but publication is not a prerequisite for inclusion in the CCDB. Any datasets that are of high quality and interest to the scientific community can be included in the CCDB.

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Neuroscience Information Framework (tool)

RRID:SCR_002894

Framework for identifying, locating, relating, accessing, integrating, and analyzing information from neuroscience research. Users can search for and add neuroscience-related resources at NIF portal and receive and RRID to track and cite resources within scientific manuscripts.

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ImageJ (tool)

RRID:SCR_003070

Open source Java based image processing software program designed for scientific multidimensional images. ImageJ has been transformed to ImageJ2 application to improve data engine to be sufficient to analyze modern datasets.

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Advanced 3D Visualization and Volume Modeling (tool)

RRID:SCR_014305

Software tool for visualizing, manipulating, and understanding data from tomography, microscopy, MRI and other imaging processes.Used to import and export options, to processes 3D image filtering and DTI based fiber tracking to visualization, volume and surface rendering, author tools for virtual reality navigation, video generation, and more.

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