Difference between revisions of "2014 Project Week:RT FormatConversions"
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* Creates python script (based on Slicer RT) for converting contours to label maps (thanks Csaba!) | * Creates python script (based on Slicer RT) for converting contours to label maps (thanks Csaba!) | ||
* Reporting module provides conversion from label map to DICOM-SEG | * Reporting module provides conversion from label map to DICOM-SEG | ||
| − | * Plastimatch | + | * Plastimatch has DICOM-RT import export |
* Will test full roundtrip conversions using QIN lung segmentation challenge datasets | * Will test full roundtrip conversions using QIN lung segmentation challenge datasets | ||
* Started creating a library of test cases with known issues (donuts, overlapping structures etc) | * Started creating a library of test cases with known issues (donuts, overlapping structures etc) | ||
Latest revision as of 04:54, 10 January 2014
Home < 2014 Project Week:RT FormatConversionsKey Investigators
Jayashree Kalpathy-Cramer (MGH)
Andras
Csaba
John Evans (MGH)
Greg Sharp (MGH)
Project Description
Objective
- Evaluate different options for converting from DICOM-seg/NIFTI/nrrd (mask) to DICOM-RT (contours) and back.
- Compare performance of Slicer RT/plastimatch/others.
Approach, Plan
- Develop a test set with range of appearance of structures
- overlapping
- donuts
Progress
- Creates python script (based on Slicer RT) for converting contours to label maps (thanks Csaba!)
- Reporting module provides conversion from label map to DICOM-SEG
- Plastimatch has DICOM-RT import export
- Will test full roundtrip conversions using QIN lung segmentation challenge datasets
- Started creating a library of test cases with known issues (donuts, overlapping structures etc)
- Will also create synthetic datasets
