OnkoDICOM was created with Radiation Oncologists to allow Radiation Oncologists to do research on DICOM standard image sets (DICOM-RT, CT, MRI, PET) using open source technologies, such as pydicom, dicompyler-core, PySide6, PIL, and matplotlib. OnkoDICOM is cross platform, open source software, and welcomes contributions. OnkoDICOM was inspired by dicompyler.
in the same way that a minimal RT Structure Set is created if none was provided, create a minimal RT Dose with a dose grid that matches the underlying images but with zero dose for each pixel/voxel.
unlike the approach to RT SS, this will save the redose.dcm immediately and then continue processing against this minimal RT Dose object (as if it had been there at initial data load).
Updated ForceLink to be able to operate against MR (the original impetus for this change was MR based Stereotactic Radio Surgery).
in the same way that a minimal RT Structure Set is created if none was provided, create a minimal RT Dose with a dose grid that matches the underlying images but with zero dose for each pixel/voxel. unlike the approach to RT SS, this will save the redose.dcm immediately and then continue processing against this minimal RT Dose object (as if it had been there at initial data load). Updated ForceLink to be able to operate against MR (the original impetus for this change was MR based Stereotactic Radio Surgery).