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04. Image Processing

Image Processing

"Image Processing" exercise for basic Life Science User Training
- smooth the image to reduce image noise using Gaussian convolution
- determine the foreground/bachkground threshold
- segment cells and apply labels
- split clumps of cells
- remove cell from image border
- calculate the features of each cell


Activity: Image ProcessingAim: calculate the size of each cell- use the Gaussian Convolution node to smooth your image to redcue image noise- use the Global Thresholder node utilizing the Otsu thresholding method- the Connected Component Analysis node segmentates the cells from the background and applies labels. In the Column Selection tab,make sure to append the new column.- the Waehlby Cell Clump Splitter node is used to segment clumps of cells. In the Column Selection tab, select "Replace first column" toreplace the Segmentation column. synthetic cellimagesNode 6Node 8Node 9Node 10 Image Reader(Table) Path to String GaussianConvolution Image Reader List Files/Folders Image Reader Activity: Image ProcessingAim: calculate the size of each cell- use the Gaussian Convolution node to smooth your image to redcue image noise- use the Global Thresholder node utilizing the Otsu thresholding method- the Connected Component Analysis node segmentates the cells from the background and applies labels. In the Column Selection tab,make sure to append the new column.- the Waehlby Cell Clump Splitter node is used to segment clumps of cells. In the Column Selection tab, select "Replace first column" toreplace the Segmentation column. synthetic cellimagesNode 6Node 8Node 9Node 10 Image Reader(Table) Path to String GaussianConvolution Image Reader List Files/Folders Image Reader

Nodes

Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: janinamothes
Created at: 2021-04-30
On NodePit since: 2022-05-05
Last update: 2024-12-17
Created with KNIME version: v4.5.2
Tags: life scienceeducationimage processingcell featuressegmentation

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