Multi-modal images and analysis
Visualizing layers of different modalities (e.g. light microscopy, µCT, EM) in a single view.Map all modalities in a single coordinate space with affine and non-linear transformations.Create transformations with rotate, scale, and translate tools.
Task system for proof-reading.Materialization of proof-read segments.
AI-based automated segmentations
Full training loop with creating annotations in WEBKNOSSOS, training a model as a background process and performing inference of a dataset.One-button solutions with pre-trained models for several segmentation tasks in EM including neurons, synapses, nuclei, mitochondria.
More segment statistics
Adding more available segment statistics such as surface areas, centroids, sphericities.
Better fluorescence support
Automatic contrast settings.Maximum intensity projection in 3D viewport.
Single-tile stack alignment
Automatically align datasets upon upload to WEBKNOSSOS.Please contact us for multi-tile alignments.
Support for importing time series data into webKnossos (5D = 3D + channels + time).
Support for selecting time points via a slider in the UI.
Calculating and showing statistics about imported and created segmentations.
Statistics will include information per segment such as volume, surface area, centroids, bounding boxes.
Zarr v3 support
Accessing dataset in the Zarr v3 format including sharding.
AI-based quick select
Draw a rectangle around an object and fill it automatically with MetaAI's Segment Anything model.
Fix split and merge errors by editing the underlying supervoxel graph of a segmentation.
Works best with segmentations from Voxelytics.
Single sign-on integration
OpenID Connect (OIDC) authentication support.
Draw a rectangle around an object and fill it automatically with a floodfill algorithm.
Organize datasets into folders, attach permissions to folders.
Add metadata to datasets, folders and search by metadata.
Stream datasets and annotations from webKnossos to other tools via the Zarr file format
Import Zarr and N5
Import Zarr and N5 datasets. Use the OME-NGFF format to define downsampling pyramids and metadata.
Support for 64-Bit segmentations.
Select custom colors for segments.
Better collaboration by enabling write access to a shared annotation within a team of annotators.
Create a volume annotation on a section, skip a few sections, draw again and interpolate in between.
Visualize agglomerate skeletons and synapses. List synaptic connections of neuron and jump from one neuron to the next.
Create, upload and access datasets and annotations from Python.