KNIME Image Processing 1.4.0 and New Integrations Released

Dear community,

We are happy to announce the release of KNIME Image Processing 1.4.0 (http://knime.imagej.net)  and of several new and already existing KNIME Image Processing extensions. KNIME Image Processing 1.4.0 and all related extensions can be installed from the KNIME 3.0.0 Trusted or Stable Community update-sites.

We are happy to answer your questions and hope to receive a lot of feedback and suggestions to further improve KNIME Image Processing.

Thank you!

KNIP Team

Changelog: KNIME Image Processing

Many New Example Workflows

  • Many new tutorials and example workflows available on the KNIME Example Server (Category: Community).

New Node: Image Writer

  • Using SCIFIO in the backend.
  • Flexible file-name selection.
  • Faster writing of tiff files.

New Node: Image Reader (Table)

  • Read images from a given location.
  • Replaces: Old Image Reader.

New Node: Image Reader

  • Allows selection of sub-series of images.
  • Allows setting of pixel type of resulting image manually.
  • Replaces: Old Image Reader.

New Node: Trackmate Tracker

  • Uses new TrackMate tracking mechanisms
  • Calculates numerical features of tracks

New Node: Feature Calculator (BETA)

  • Many new feature types available (Zernike, Moments, 3D Haralick, 3D Geometric, Local Binary Patterns, Tamura, ...)
  • Redesign of user interface
  • Replaces: Image Features, Image Segment Features and Segment Features

New Node: Labeling Editor

  • Allows editing the labels (=segments) on labelings (=segmentations). For example you can provide the classes of objects for subsequent machine learning algorithms.

New Node: Colorspace Converter

  • Converts images from one colorspace into another colorspace
  • For example: RGB to HSB

Refactoring of Table Cell Viewer

  • Rename to Image Viewer
  • Redesign of the complete viewer frame
  • Allows displaying multiple images next to each other (with synchronized view) or overlayed
  • Faster navigation through tables

General Improvements

  • Subsetselection via Flow-Variables
  • Allow multiple Sigma in Gauss
  • Better caching of data-cells (to avoid heavy IO)
  • PNGImage to ImgPlus: Allow to set value for transparent values

Changelog: Other Integrations

New Integration: KNIME Python Extensions

New Integration: KNIP Ilastik Integration

Updated Integration: KNIP Tess4J Integration

Updated Integration: KNIP CellProfiler Integration

Updated Integration: KNIP ClearVolume Integration

Infos for Developers

Full list of changes: https://github.com/knime-ip/knip/issues?page=2&q=is%3Aissue+milestone%3A1.4.0+is%3Aclosed

Hi Christian,

 

this is great!!

 

Looking forward to use it :)

 

Cheers

 

manuel