Biolucida®for Research

Manage big image data
MBF Bioscience > Biolucida®for Research

Product Overview

Biolucida is a hub for 2D and 3D big image data. It stores all of your 2D and 3D image data and metadata in a secure, permanent location accessible via the web. Images can be acquired with slide scanners or microscope systems, and can be any size – Biolucida is built to store, organize, and serve huge image collections. The possibilities are endless with Biolucida: share images with collaborators, include large image sets from published papers, contribute standardized data to public image data repositories, or analyze images on any computer with Neurolucida 360, Stereo Investigator, BrainMaker. You will always have control over your images and access to them.

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Key Benefits

Biolucida allows researchers to share and standardize data via an intuitive yet powerful web interface. Create and share collections of annotated image data and control access with a few clicks. Content from previous research can also be included via image inclusion or simple HTML weblinks.

Biolucida easily integrates with an institute's IT architecture using secure and current standard web technologies. Biolucida utilizes extensive client and server optimizations to ensure the fastest image access experience, even at peak internet usage times.

System Requirements for Biolucida Viewer

Operating System

  • Windows 10, 64-bit
  • OSX 10.9 or later
RAM

At least 6 GB

System Requirements for Biolucida Server

Operating System

  • Linux (CentOS 6 or 7)
  • Windows server 2016 or later
Processor

minimum 4-cores for 2D/3D  whole slide images

RAM

minimum 8GB with connectivity of 1 Gbps or great

Biolucida exists as a standard, easily maintained WAMP/LAMP stack and proprietary C++ derived software.

Case Study
American Association of Anatomists Launches Virtual Microscopy Database powered by Biolucida
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Case Study
Medical Schools Take Learning Online with Biolucida During COVID-19
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Castro, A., Becerra, M., Jesús Manso, M., & Anadón, R. (2015). Neuronal organization of the brain in the adult amphioxus (Branchiostoma lanceolatum): A study with acetylated tubulin immunohistochemistry. Journal of Comparative Neurology, n/a-n/a. doi: 10.1002/cne.23785. http://dx.doi.org/10.1002/cne.23785

Chen, C.-C., Winkler, C. M., Pfenning, A. R., & Jarvis, E. D. (2013). Molecular profiling of the developing avian telencephalon: Regional timing and brain subdivision continuities. Journal of Comparative Neurology, 521(16), 3666-3701. doi: 10.1002/cne.23406. http://dx.doi.org/10.1002/cne.23406

Condro, M. C., Matynia, A., Foster, N. N., Ago, Y., Rajbhandari, A. K., Jayaram, B., . . . Waschek, J. A. (2016). High-resolution characterization of a PACAP-EGFP transgenic mouse model for mapping PACAP-expressing neurons. Journal of Comparative Neurology, n/a-n/a. doi: 10.1002/cne.24035. http://dx.doi.org/10.1002/cne.24035

Daniel, H., Ester, D., P., U. J. F., L., J. A., Timothy, S.-G., A., D. G., . . . Scott, K. J. (2018). A 3D MRI-based atlas of a lizard brain. Journal of Comparative Neurology, 0(ja). doi: doi:10.1002/cne.24480. https://onlinelibrary.wiley.com/doi/abs/10.1002/cne.24480

Gerfen, Charles R., Paletzki, R., & Heintz, N. (2013). GENSAT BAC Cre-Recombinase Driver Lines to Study the Functional Organization of Cerebral Cortical and Basal Ganglia Circuits. Neuron, 80(6), 1368-1383. doi. http://linkinghub.elsevier.com/retrieve/pii/S0896627313009197

Haeussner, E., Aschauer, B., Burton, G. J., Huppertz, B., Edler von Koch, F., Müller-Starck, J., . . . Frank, H.-G. (2015). Does 2D-Histologic identification of villous types of human placentas at birth enable sensitive and reliable interpretation of 3D structure? Placenta. doi: http://dx.doi.org/10.1016/j.placenta.2015.10.003http://www.sciencedirect.com/science/article/pii/S0143400415300631

Hannibal, J., Christiansen, A. T., Heegaard, S., Fahrenkrug, J., & Kiilgaard, J. F. (2017). Melanopsin expressing human retinal ganglion cells: Subtypes, distribution and intraretinal connectivity. Journal of Comparative Neurology, n/a-n/a. doi: 10.1002/cne.24181. http://dx.doi.org/10.1002/cne.24181

Hof, P. R. (2014). Passages 2014. Journal of Comparative Neurology, 522(1), 1-5. doi: 10.1002/cne.23474. http://dx.doi.org/10.1002/cne.23474

Hooks, B. M., Papale, A. E., Paletzki, R. F., Feroze, M. W., Eastwood, B. S., Couey, J. J., . . . Gerfen, C. R. (2018). Topographic precision in sensory and motor corticostriatal projections varies across cell type and cortical area. Nature Communications, 9(1), 3549. doi: 10.1038/s41467-018-05780-7. https://doi.org/10.1038/s41467-018-05780-7

Iacono, D., Lee, P., Edlow, B. L., Gray, N., Fischl, B., Kenney, K., . . . Perl, D. P. (2019). Early-Onset Dementia in War Veterans: Brain Polypathology and Clinicopathologic Complexity. Journal of Neuropathology & Experimental Neurology. doi: 10.1093/jnen/nlz122. https://doi.org/10.1093/jnen/nlz122

Karten, H. J., Glaser, J. R., & Hof, P. R. (2013). An important landmark in scientific publishing. Journal of Comparative Neurology, 521(8), 1697-1698. doi: 10.1002/cne.23329. http://dx.doi.org/10.1002/cne.23329

Lipovich, L., Hou, Z.-c., Jia, H., Sinkler, C., McGowen, M., Sterner, K. N., . . . Wildman, D. E. (2015). High-throughput RNA sequencing reveals structural differences of orthologous brain-expressed genes between western lowland gorillas and humans. Journal of Comparative Neurology, n/a-n/a. doi: 10.1002/cne.23843. http://dx.doi.org/10.1002/cne.23843

O'Connor, N., Tappan, S., & Glaser, J. (2014). How to Prepare Neuroanatomical Image Data Current Protocols in Neuroscience (Vol. 69): John Wiley & Sons, Inc.

Ogilvie, R., Sawyer, R., Greenwold, M., Bao, W., & Thompson, J. (2014). Evolution of a cross-institutional asynchronous online 500 level college histology course with interactive lectures and virtual lab component (530.1). The FASEB Journal, 28(1 Supplement). doi. http://www.fasebj.org/content/28/1_Supplement/530.1.abstract

Pastrana, E. (2014). A genetic handle on brain circuits. Nature Methods, 11, 128. doi. http://www.nature.com/nmeth/journal/v11/n2/full/nmeth.2829.html

Sakano, H., Zorio, D. A. R., Wang, X., Ting, Y. S., Noble, W. S., MacCoss, M. J., . . . Wang, Y. (2017). Proteomic analyses of nucleus laminaris identified candidate targets of the fragile X mental retardation protein. Journal of Comparative Neurology, n/a-n/a. doi: 10.1002/cne.24281. http://dx.doi.org/10.1002/cne.24281

Samal, N., & Prakash, R. V. K. (2019). Randomized cross-over study and a qualitative analysis comparing virtual microscopy and light microscopy for learning undergraduate histopathology. Indian Journal of Pathology and Microbiology, 62(1), 84. doi. 

Download our product sheet here.

 

Who Is Using Biolucida?

More than 150,000 students have used Biolucida for Medical Education to study histology and histopathology

Cited in Peer Reviewed Scientific Publications

Biolucida’s utility is underscored by the number of references it receives in the worlds most important scientific publications.

Frequently Asked Questions (FAQ)

How does Biolucida work?

Biolucida consists of 3 parts: a server computer, Biolucida server software, and the Biolucida viewer. Together, the server computer and server software constitute a virtual central library where your slides are maintained and served. Biolucida can integrate into existing IT infrastructure, it can be set up in another location, or it can be hosted in the cloud with Amazon Web Services.


The Biolucida server software allows educators and students to navigate through large images quickly — there is no waiting for images to download. This
software runs behind the scenes and is not visible to users.


The viewer is the software application that instructors and students use to view, access, and share virtual slides. The viewer can run on any computer (PC or Mac) connected to the internet.

How large can the files be?

Biolucida efficiently serves very large virtual slides. A typical single image size is 10-50 gigabytes, but Biolucida can easily handle an image that exceeds of
terabytes.

Which computer platforms do you support?

The Biolucida viewer runs on Mac and PC, and the Biolucida server software runs on Windows and Linux. The Biolucida web browser viewer also allows viewing
slides on mobile platforms such as iPads.

Can I use images acquired with my slide scanner or my confocal microscope?

Yes, Biolucida supports images acquired with slide scanners from companies such as Huron, Aperio, Leica, Olympus, Zeiss and Hamamatsu. It also supports
images and image stacks acquired with confocal microscopes from companies such as Zeiss, Olympus, and Leica.

Can I easily compare images?

Yes, Biolucida lets you easily compare multiple images simultaneously.

Can I focus through 3D virtual slides?

Yes, Biolucida supports 3D virtual slides and allows users to focus through image planes just like a microscope.

Testimonials

Robust Professional Support

Our service sets us apart, with a team that includes Ph.D. neuroscientists, experts in microscopy, stereology, neuron tracing, and image processing.  We’ve also developed a host of additional support services, including:

  • Forums
    We have over 25 active forums where open discussions take place.
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  • On-Site/Training
    We’ve conducted over 750 remote software installations.
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  • Webinars
    We’ve created over 55 webinars that demonstrate our products & their uses.
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Request an Expert Demonstration

We offer a free expert demonstration of Biolucida. During your demonstration you’ll also have the opportunity to talk to us about your hardware, software, or experimental design questions with our team of Ph.D. neuroscientists and experts in microscopy, neuron tracing, and image processing.