Sorry for late reply, @dlrubin
It’s still in its infancy, but I released the working draft of sample data of R-CDM here
( Oncology radiology imaging integration into CDM ).
[Annotation / Report in Radiology]
I know annotation data and ROI are very important, and I need to learn from AIM project. But as you said, I do not have the data containing information about this, now. I suggested the extension model of ‘NOTE’ table for storing radiology report ( https://github.com/OHDSI/CommonDataModel/issues/172 ) , and I hope this proposal to be adopted in OMOP CDM v6.0.
[Question1: imaging for stroke and standardization of DICOM headers]
We leverage information fro DICOM headers, but we cannot totally dependent on it. These informations are not standardized as you said. The solution for identifying the specific phases in radiology images should be developed one by one in each institution for each radiology images. We found out which rule we should use to identify phases in brain CT by browsing DICOM headers.
Again, R-CDM project is in its infancy.
I am really pleased if you can join this research. I can make CNN model for MRI (actually it is much easier to use brain MRI rather than CT, because there is much more open-source code analyzing brain MRI). But I think it would be much more difficult to standardize MRI procedure (The phases are so complicated in brain MRI. But we can start with only T1, T2 and FLAIR for the pilot study.)
[Question 2]
PLP ecosystem requires features in the format of n-dimensional vectors. Actually, I need to figure out how to make feature vectors… It can be done through supervised learning or unsupervised learning. But I do not have concrete idea for this for now.