Closed Ivan-E-Johnson closed 6 months ago
This issue was significantly expanded. Together with @Ivan-E-Johnson we were able to extend the functionality of the system towards the Sprint 3 Minimum Viable Product.
Here are the new aspects covered under the issue and branch #118
Furthermore, this issue ties to the following user stories:
If this feature request related to a problem? Please describe.
Our current process for downloading stable instances from our Orthanc DICOM server is manual and time-consuming. This issue becomes apparent when dealing with large datasets or when trying to ensure that only the most stable and verified instances are downloaded for further processing or analysis. An automated or more efficient method of identifying and downloading these instances would significantly improve our workflow, reduce errors, and save time.
Rationale
Implementing a feature that automates the identification and downloading of stable instances from Orthanc would be highly beneficial for several reasons. Firstly, it would streamline our data handling processes, making them more efficient and less prone to error.
Implementation Ideas PyOrthanc
Additional Context Next step in connecting example tool to orthancs