The KNIME Image Processing Plugin allows you to read in more than 120 different kinds of images (thanks to the Bio-Formats API) and to apply well known methods on images, like preprocessing. segmentation, feature extraction, tracking and classification in KNIME. In general these nodes operate on multi-dimensional image data (e.g. videos, 3D images, multi-channel images or even a combination of them), which is made possible by the internally used ImgLib2-API.
Several nodes are available to calculate image features (e.g. zernike-, texture- or histogram features) for segmented images (e.g. a single cell). These feature vectors can then be used to apply machine learning methods in order to train and apply a classifier.
Currently the Image Processing Plugin for KNIME provides ca. 100 nodes for (pre)-processing, filtering, segmentation, feature extraction, various views (2D, 3D), etc. and integrations for various other image processing tools are available (see used and integrated libraries)
Future directions include a full, bidirectional integration of ImageJ2. Such an integration allow the users to use directly use/update ImageJ2 Plugins inside KNIME as well as recording and running KNIME Workflows in ImageJ2. Please see ImageJ2 Integration (BETA) for more information.
We moved all our Example Workflows to the KNIME Example Server: https://www.knime.org/example-workflows. In the category 099_Community/ you will find example applications & tutorials for all our integrations including information about the content of the workflow and how to get the workflow running.
If you have suggestions, problems, etc. don't hesitate to write in the our forum or contact us! We are glad to help you.
|Christian Dietz||Chair for Bioinformatics and Information Mining, University of Konstanz|
The KNIME Image Processing nodes are released under GPLv3.