One-stop solution for Volume Electron Microscopy

Import your large 3D data with Python. Effortlessly explore, annotate, and collaborate on electron microscopy data.

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Streamlining Volume EM Analysis with WEBKNOSSOS

Upload your Volume EM data, and WEBKNOSSOS will seamlessly guide you through the entire analysis process. Experience hassle-free pre-processing, collaborative visualization and annotation, effortless data management and sharing, as well as efficient data segmentation and proofreading.

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WEBKNOSSOS in Volume Electron Microscopy

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Visualize massive datasets–from anywhere

Upload your 2D or 3D datasets to WEBKNOSSOS and access them from wherever you have an internet connection. Enjoy the fast browsing speeds of WEBKNOSSOS.
Proven image streaming for petabyte-sized data and beyond.

Example: EM data from Motta et al. 2019, segmentation by scalable minds

Securely share data with collaborators

Invite collaborators or annotators into your organization. Manage users in teams and set role-based dataset permissions.

Send token-protected links to outside collaborators or reviewers.

The data stays safe in WEBKNOSSOS: By default users are not allowed to download the data unless you enable it.

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Visualize registered light and electron microscopy together

Use CLEM to collect both functional information given by the Fluorescent Microscopy and structural information given by Electron Microscopy. 
Overlap the layers on WEBKNOSSOS and turn them on and off as you analyzeyour data.

Raw SBEM high-res data - Mouse lateral parietal association cortex P46Drawitsch et al.

Analyze your data directly online

Take measurements within your data. Mark interesting locations or bounding boxes. Create segmentations with manual brush or trace tools. Visualize segmented objects as mesh through the integrated mesh generation.

Create skeleton annotations of neurons, measure their path lengths and organize these skeletons in hierarchical groups. Try out the unique flight mode for high-speed tracing of axons or dendrites.

Use the task/project system to manage annotation projects. If you don't have annotators, you can hire our annotation services directly through WEBKNOSSOS.

Example: Annotations and EM data from Schmidt et al. 2017

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Need alignment or registration?

Check out dataset alignment services!

Publish datasets to the community–when ready

Tell your story with data. Link directly from a figure in your publication to that location in WEBKNOSSOS. Readers will be able to explore your annotations and understand the context of your findings. 

WEBKNOSSOS is an excellent platform for publishing large datasets including segmentations and training data. Viewers can freely browse through your data and build upon it. 

Example: Figures with wklink.org short-links from Motta et al. 2019 (Science)

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Interoperate with your favorite tools

Download your data and annotations from WEBKNOSSOS to work with them in other tools. WEBKNOSSOS supports standard formats (e.g. TIFF, STL, N5/ZARR, CSV) for exports.

Work with the webKnossos file formats in Python or MATLAB, with our open-source libraries. Learn more in the user documentation.