KNOSSOS 5.1

New Features:

Annotation

• Mesh slice in orthogonal viewports. Previously the mesh was only visible in the 3D view.
• Mesh transparency can be adjusted.
• Skeleton and Segmentation table entries are now copyable to clipboard.
• Skeleton nodes table: A new context menu entry lets you select all trees that contain selected nodes.
• Segmentation: Rendering of borders of segmentation objects can be toggled off now.

Settings

• Settings per annotation file: Just add a settings.ini to your .k.zip.
• Beginning with this version, settings are maintained and compatible between different versions.

Datasets

• Support for new NeuroData Store url naming scheme (previous scheme still works): /ocp/ca/ ↦ /nd/sd
• We added a new default dataset

Other

• Cheatsheet: An informative side panel with an overview of the active work mode including shortcuts and links to related settings.
• Snapshot preview: Let’s you copy to clipboard, no need to save to file.
• There’s now a progress bar indicating network activity.

Bug Fixes:

• Merging trees now correctly merges their meshes, too.
• The display of translucent meshes has been improved.
• Segmentation bucket fill: Buggy behavior at vp and movement boundaries have been fixed. Performance of the bucket fill has been improved.
• Some issues when filtering in the annotation tables have also been fixed.

Launching an AppImage

Add the executable flag to it first, e.g. with

chmod +x linux.KNOSSOS.nightly-xxxxxxxx.AppImage

or open the file’s properties by right-clicking on it in your file browser.

nightly-dev

development binaries from the latest successful commit of every branch (including debugging information)

the win.master-KNOSSOS.nightly.exe here is equivalent to the normal nightly but with debug infos

nightly

Nightly releases for every new commit of the master branch.

(the date is older so it lists the official release first)

KNOSSOS 5.0.1

Enhancements

• Improved performance of operations on large number of trees/nodes
• Keep orientation when switching between equivalent datasets
• Adapted scale bar length to display »rounder« values
• Added base grid for 3D viewport’s boundary box

Fixes

• Node view selection only worked in one work mode
• Corrected task management display
• Fixed arbitrary viewport regression (viewport sometimes went mostly black)
• Fixed zoom-in shortcuts

Platform Notes

• The AppImage does not run on Ubuntu versions < 16 LTS and on Debian versions < stretch.

KNOSSOS 5

Features

Dataset:

The dataset loading mechanism was updated to support a wider range of dataset configurations, including

• local jpeg-compressed raw datasets (additionally to remote ones)
• customizable dataset cube sizes
• various dataset backends. For example a dataset url containing “/ocp/ca/” will be interpreted as an open connectome dataset.

Mesh:

It is now possible to load triangle meshes into KNOSSOS. Meshes are a set of vertices, colors and indices. In KNOSSOS they are associated to one skeleton tree and are displayed inside the 3D viewport.

Simply insert a mesh file (.ply) into a KNOSSOS annotation file (.k.zip) and it will be loaded with it.

Visit our wiki to read about the exact file format.

Inside KNOSSOS you can jump to specific areas of interest: Just click on the mesh location and press S.

Skeletonization:

• Trees are now traversed along the edges (depth-first-search) with X and Shift+X (previously, traversal order was defined by node ID).
• You can now enable anti-aliasing for a smoother skeleton visualization.
• Node comments can be displayed directly inside viewports. This should improve your orientation.

Synapses feature:

For neural annotations you can now create synapses with a synaptic cleft as
well as pre- and postsynapse:

1. Simply perform your ordinary skeletonization.
2. On encountering a synapse, end the current tree with Shift+C. The last placed node is marked as pre-synapse.
3. Now annotate the synaptic cleft by placing nodes along it as usual. When you are finished, press C to end the cleft.
4. The next placed node will be marked as post-synapse.

Properties feature:

Until now additional information about trees and nodes had to be crammed into the respective object’s comment section. This became unreadable and hard to parse very quickly.

So we introduced customizable and visualizable properties. Properties are either simple text or textual or numerical key value pairs.

Numerical node properties can be highlighted inside the viewports: You can choose to scale radius by property value or to map property value to color map value, or both.

Segmentation:

• You can now perform bucket fills, with the viewport being its maximum scope (middle mouse button)
• Segmentation operations are now possible in all magnifications instead of only in mag 1.
• The form of the segmentation brush is now aligned with the image pixels.
• The color of segmentation objects can be changed.

Annotation in general

• You can use the dropdown in the toolbar to quickly switch between different
  work modes, e.g.:
• “Tracing Advanced“: More complex tracing operations such as unlinked
  nodes or multiple trees have been moved into this separate work mode,
  so that ordinary tracing has become simpler and less error-prone.
• “Merge Tracing”: In this mode skeletonization and segmentation are
  performed simultaneously: Place nodes on segmentation sub-objects to
  automatically merge them together. The result will be a classical
  skeletonization in which each tree corresponds to one merged
  segmentation object.
• “Review”: A segmentation proof-reading mode in which painting and
  merging are disabled to prevent accidental modifications.
  Skeletonization serves as review annotation.
• A movement area can be defined to restrict your work to a specific location
  of interest. Everything outside this area is darkened to an adjustable
  degree and cannot be modified.
• Spacebar hide: The viewport is often cluttered with nodes, edges,
  segmentation overlay and viewport tools. Hold the spacebar and everything
  except the raw dataset will be hidden for this duration.

Python Plugin Manager:

KNOSSOS now has a plugin manager, allowing you to write and share plugins written in Python in an online repository.

For example you can write custom GUI elements, create annotations programmatically or utilize your own algorithms. The idea is to customize KNOSSOS and make it fit your unique workflows.

As a starting point and reference we have a set of plugins available at https://github.com/knossos-project/knossos-plugins.

The Manager can be found under the “Scripting” menu entry.

Viewports:

• You can now take viewport snapshots of varying resolutions. The snapshots can be configured to decide what should be visible in them, e.g. only raw data, segmentation, skeletonization etc.
• Viewports can be undocked and positioned independently of the KNOSSOS window. Especially, multi-screen workplaces might find it useful to place a fullscreen viewport onto one screen.
• A scalebar in every viewport shows the dataset’s physical dimensions.
• The 3D viewport now supports wiggle stereoscopy, just hold W. Wiggle stereoscopy is a computer graphics method to make the 3-D nature of structures better recognizable.
• Inside the plane viewports KNOSSOS now shows information about what’s underneath your mouse cursor:
  • The position inside the dataset (shown in the lower left corner)
  • The segmentation object id at that position (shown below the segmentation table in the annotation widget)
• A fourth viewport with arbitrary orientation can be turned on. One of the purposes of an arbitrary view is to automatically orient itself orthogonally to the skeleton while tracing. This feature is still experimental.

User Interface:

• In the Annotation widget we replaced the previous skeleton view that caused performance problems for large skeletons. The new table also supports sorting.
• Skeleton as well as segmentation tables consume less space. There is only
  one segmentation table, but if overlapping objects are selected, they are
  shown in an extra table.
• We moved various options into preferences widget to reduce the number of
  floating windows in KNOSSOS.
• When loading a dataset, you can specify a field of view for the viewports.
• We tried to make all shortcuts visible in the user interface.
• Comment shortcuts have moved from the F keys to the number keys.

Zoom:

• The zoom interface now supports dynamic switching between magnifications.
  A value of 100% represent the highest magnification.
• In the 3D viewport KNOSSOS now zooms in at the cursor position. To inspect
  something closer, simply let the mouse cursor hover over it while zooming.
• In conformance with most other user interfaces, Ctrl++, Ctrl+- and
  Ctrl+0 are now the shortcuts for zooming in, out or to reset zoom.

Other improvements

• KNOSSOS does not consume as much computing power anymore while running in the
  background.

KNOSSOS 4.1.2

Noteworthy Changes

• merging trees resulted in a crash
• range delta and bias did not work properly
• more intuitive node selection
• performance improvements
• internal and visual improvements to the Heidelbrain integration

The *.deb package apparently doesn’t work on many systems.
If it doesn’t, try the previous release instead or quickly install either the release version or a git snapshot of KNOSSOS using junest.

KNOSSOS 4.1.1

Fixed issues

• Segmentation overlay is disabled by default (less resource consumption).
• Extracting a connected component as a new tree works again.
• Jumping to next node now respects the comment filter from the annotation window.
• Lower idle cpu usage
• No broken movement after loading a new dataset while in magnification > 1
• The 3D segmentation brush is now visible.
• Dataset loading widget is more intuitive.
• File handling on Mac
• Node selection on MacBook Retina

win64-standalone and win32-standalone require an already installed python distribution.
win64-Setup and win32-Setup contain an official python 2.7 installer.
An AUR package is also available.

KNOSSOS 4.1

This version introduces

• volume annotation through segmentation
• a Python scripting interface for custom plugins
• an important bug fix for the time tracking in KNOSSOS

and many more features and changes! See the changelog for details.

win64-standalone and win32-standalone require an already installed python distribution.
win64-Setup and win32-Setup contain an official python 2.7 installer.

KNOSSOS 4.0.1

New Mac Version

We now have a Mac release!
Please note following differences between the Mac version and the other versions:

• For the actions under "Edit Skeleton" you need to hold the "fn" key additionaly. For example, to add a new tree you would press: fn + C.
• There are no Buttons in the Skeleton Viewport, so in order to rotate there, open the context menu with: Cmd + right click.
• Generally, commands that require to hold the "Ctrl" key require to hold the "Cmd" key instead, e.g. to move around a viewport perform Cmd + Alt + left mouse click and move.

We are still working on unifying the behaviour on all platforms. Please let us know if you find any more unexpected behaviour by opening an issue here:

https://github.com/knossos-project/knossos/issues

Changelog

• press 5 to temporarily display the uncompressed data of compressed remote dataset. Current compression is visible in the Zoom and Multiresolution widget
• fixed a major performance problem on systems, where vsync was not disabled
• downloaded files from remote datasets are now deleted after loading

First KNOSSOS Qt Release

KNOSSOS v4.0 - Change Log

KNOSSOS is a software tool for the visualization and annotation of 3D image data and was developed for the rapid reconstruction of neural morphology and connectivity.

General Information

Release Date: Date 03.06.2014

KNOSSOS 4.0 is a milestone release with a completely reworked graphical user interface based on
the QT framework.

Homepage: http://www.knossostool.org/
Project host: https://github.com/knossos-project/

Roadmap:
v4.1:

• Interactive Python scripting
• Volume annotation and visualization of large scale segmentation data

Known Bugs

UI Improvements

• Nicer look and feel
• Native file dialogs and ui elements
• Restructured menu:
  • Icons and shortcut information in the menu bar
  • Current workmodes are marked with a check
  • A Toolbar with a collection of important widgets
  • Restructured Viewport Settings Widget
• Tooltips
• Integrated documentation
• Unsaved changes are indicated with an (*) in the titlebar

Features

Tracing:

• Integration of client-server based task management (with a Python django backend), that allows annotators to efficiently submit
  their tracings to a database.
• Extensive filtering and listing of trees and nodes (with regular expression support) based on comments and other properties.
• Visual selection and operations on groups of nodes in all viewports.
• Show only selected trees.

Dataset:

• Real time arbitrary angle slicing for voxel data (use eg l or k for rotations).
• Datasets can now be streamed from remote server locations (http based, works well for connection speeds > 10 MBit/s with compression)
• Datasets can be compressed (each datacube individually) with JPG2000 or JPEG with real time decompression during the navigation (multi-threaded).
  Typical values for 3D EM datasets without obvious compression artefacts are ~1 bit / voxel. Lossless compression is also supported.
• On-the-fly dataset changes possible under File->Load Dataset, no more Python Launcher required.
• KNOSSOS remembers the last used dataset and loads it on launching.

Skeleton:

• Multiple skeletons can now be loaded at the same time (select more than one in the file dialog).
• Load Skeletons by drag'n dropping them into KNOSSOS.

Changes

• The Python Launcher has been removed.
• Moving Viewports around now works with Ctrl+AltLeft mouse drag
• The synchonization of multiple KNOSSOS instances is currently not supported any more
• The format for custom preferences is now saved in a key value file structure (.conf)
• Default Folder for Skeleton Files is now in the standard data location (i.e for Windows: %AppData%/MPIMF and for Linux: /home/user/.local/share/data/MPIMF)
• A Mac OS X Version (>= version 10.9) will be available soon.
• Debian Package for Linux (Tested on Ubuntu [i386/amd64](>= version 12))