image processing workflow (KNIME GmbH)
90
Structured Review
KNIME GmbH
image processing workflow
Image Processing Workflow, supplied by KNIME GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/processing+workflow/image+processing+workflow/pmc07469687-322-4-1
Average 90 stars, based on 1 article reviews
Image Processing Workflow, supplied by KNIME GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/processing+workflow/image+processing+workflow/pmc07469687-322-4-1
Average 90 stars, based on 1 article reviews
image processing workflow - by Bioz Stars,
2026-09
90/100 stars
Images
1) Product Images from "Integration of the ImageJ Ecosystem in the KNIME Analytics Platform"
Article Title: Integration of the ImageJ Ecosystem in the KNIME Analytics Platform
Journal: Frontiers in computer science
doi: 10.3389/fcomp.2020.00008
Figure Legend Snippet: Side-by-side comparison of ImageJ macro with KNIME workflow using KNIME Image Processing nodes.
Techniques Used: Comparison
Figure Legend Snippet: Quantitative analysis of subcellular structures. To analyze the consequences of disrupting the cytoskeleton on matrix adhesion focal adhesion complex formation is visualized using TIRF imaging. A KNIME workflow was leveraged to define the number of focal adhesion complexes at the periphery of the cell vs. within the center of the cell using sequential steps with discrete objectives: I. Read file in, II. Processing of the images into labels that capture the individual focal adhesion complexes, III. Arithmetic on the labels to obtain the characteristics (features) for classification, IV. Classification of the labels using extracted features, V. Visualization of the classified focal adhesion complexes (periphery vs center). Note that the output of this pipeline is a combination of visualization and quantitation. Both of these can be leveraged for further analysis.
Techniques Used: Imaging, Quantitation Assay
Figure Legend Snippet: Quantitative analysis of histological stain. The histological staining of a cell adhesion marker (CD166) related to tumor invasion and metastasis demonstrates significant variation across patient samples. As in user case #1, the KNIME workflow was divided into sequential steps that complete discrete objectives: 1) read in file , 2) pre-processing of the images and their annotation in preparation for analysis using ImageJ2 functionalities, 3) pixel classification using Weka-bases machine learning functionality, 4) post-classification processing of image data to labels that correspond to ‘positive’, 5) compilation of labels, images and annotations, 6) visualization of the quantitation by overlaying the labels with the original image.
Techniques Used: Staining, Marker, Quantitation Assay
Figure Legend Snippet: A KNIME workflow for channel-shift correction and particle tracking. The positions of bead detections are shown in three-pane scatter plots, before (left) and after (right) applying channel-shift correction. The density plots show absolute distances between apparent bead locations of two channels before (red) and after (cyan) correction.
Techniques Used:
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