Dear KNIME Community
We have a work in which I have to detect micro calcifications. The data I have are a csv-file with the following structure:
"x" and "y" represent the position of the pixel (in pixels), "abs" is the absorption intensity, "dci" is the scattering intensity. "cal" is the likelihood that the value is part of calcification (not normalized). In the attachment you find the picture with the absorption values (abs_picture.png) and the cal_picture.
If you want to download the csv file I can only provide my dropbox link, since it is larger than the 4 MB allowed to upload in the forum (https://www.dropbox.com/s/1syg9y6aisxyhg0/combined_image_with_labels.csv?dl=0).
The goal is the identify the cal pixels from the abs, dci channels of the given and surrounding (x-x')^2+(y-y')^2<R^2 pixels. Therefore a receiver operating characteristic (ROC) curve was made, which compares the processed image with the cal_picture image. (See workflow microcalcificationworkflow.zip, open the meta node Calculate ROC area and view the output of the ROC Curve).
We tried to get a high value as close as possible to 1.0. With the workflow microcalcification_update we reached 0.6581 for the absorption. We try to get a better value and also a good value for the scattering data.
Do you have an idea how we can reach this? Any help is very appreciated.
Matthias, Vittora, Federica