segmentationIRAEMM_ONKO_retro_DM.json 2.5 KB

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  1. {
  2. "setVariables":["__tempBase__","__segBase__","__segModelPath__","__roiFile__","__petFile__","__ctFile__","__segFile__","__modelName__"],
  3. "setVariablesComment":"this variables will get updated with local values like home and can be used to set variables further on",
  4. "__tempBase__":"__home__/temp/iraemm",
  5. "__segBase__":"/home/studen/software/src/irAEMM/segmentation",
  6. "__segModelPath__":"/home/studen/software/src/iraemmsegmentationmodels",
  7. "__roiFile__":"testMask.nii.gz",
  8. "__ctFile__":"testCT.nii.gz",
  9. "__petFile__":"testPET.nii.gz",
  10. "__segFile__":"segmentation.nii.gz",
  11. "__modelName__":"DM_defaults.DM_train_VISCERAL16_Fold1.final.2019-10-01.07.46.19.932616.model.ckpt",
  12. "tempBase":"__tempBase__",
  13. "model":"__model__",
  14. "project":"IPNUMMretro/Study",
  15. "targetSchema":"study",
  16. "targetQuery":"Imaging1",
  17. "viewName":"default",
  18. "participantField":"PatientId",
  19. "segmentationSchema":"study",
  20. "segmentationQuery":"organSegmentationsDM",
  21. "reportQuery":"reportImages",
  22. "reportSchema":"lists",
  23. "percentileQuery":"SUVQuantilesDM",
  24. "imageDir":"preprocessedImages",
  25. "version":"v2test",
  26. "versionNumber":"2",
  27. "images":{
  28. "CT":{
  29. "queryField":"ctResampled",
  30. "tempFile":"__ctFile__"},
  31. "PET":{
  32. "queryField":"petResampled",
  33. "tempFile":"__petFile__"},
  34. "patientmask":{
  35. "queryField":"ROImask",
  36. "tempFile":"__roiFile__"},
  37. "segmentation":{
  38. "suffix":".nii.gz",
  39. "tempFile":"__segFile__"}
  40. },
  41. "replacePattern":{
  42. "__workDir__":"__tempBase__",
  43. "__roi__":"__tempBase__/__roiFile__",
  44. "__pet__":"__tempBase__/__petFile__",
  45. "__ct__":"__tempBase__/__ctFile__",
  46. "__seg__":"__segFile__",
  47. "__cnnModelPath__":"__segModelPath__",
  48. "__model__":"__modelName__"
  49. },
  50. "nnUNet":{
  51. "ModelId":"501",
  52. "configuration":"3d_fullres",
  53. "env":{
  54. "nnUNet_raw_data_base":"__tempBase__",
  55. "nnUNet_preprocessed":"__tempBase__",
  56. "RESULTS_FOLDER":"/home/studen/software/src/iraemmsegmentationmodels"
  57. }
  58. },
  59. "deepmedic": {
  60. "config":{
  61. "model":{
  62. "template":"__segBase__/model/modelConfig.cfg.template",
  63. "out":"__tempBase__/modelConfig.cfg"
  64. },
  65. "test":{
  66. "template":"__segBase__/test/testConfig.cfg.template",
  67. "out":"__tempBase__/testConfig.cfg"
  68. },
  69. "predictions":{
  70. "template":"__segBase__/test/testNamesOfPredictions.cfg.template",
  71. "out":"__tempBase__/testNamesOfPredictions.cfg"
  72. },
  73. "CT":{
  74. "template":"__segBase__/test/testChannels_CT.cfg.template",
  75. "out":"__tempBase__/testChannels_CT.cfg"
  76. },
  77. "ROI":{
  78. "template":"__segBase__/test/testRoiMasks.cfg.template",
  79. "out":"__tempBase__/testRoiMasks.cfg"
  80. }
  81. }
  82. }
  83. }