The material for the Quantitative Big Imaging course at ETHZ for the Spring Semester 2018
View the Project on GitHub kmader/Quantitative-Big-Imaging-2018
The data for the example can be downloaded from here and extract the train.zip file
Open the file in Archive Manager and extract the data to /scratch
(only on D61.1 machines)
For each .tif file there is an associated _mask.tif corresponding to the ground truth
Many of these workflows are fairly complicated and would be time consuming to reproduce, follow the instructions here for how to import a workflow from the zip files on this site
If you load a workflow and get an error message, click on the details button. If it says ‘Node … not available’ it means you need to update your ‘Image Processing Extensions’ follow the instructions below to perform this update: instructions
Steps are shown in normal text, comments are shown in italics.
Knime Basics: here
Use workflow variables: here
The task from the lecture of identifying the nerve in the ultrasound image
.
We thus have these data loaded in the workflow as the image and ground truth respectively.
The ROC curve’s discussed in the last lecture we will use as a tool for evaluating our accuracy for the rest of the course. An example work-flow is below to generate the above curve.
Download the workflows here
Parameter Optimization Loop Start
node to find the best filter size to maximize the ROC area