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Datasets:
DEPICT-RH
/
Multimodal-HC

Tasks:
Any-to-Any
Image-to-Image
Image Segmentation
Size:
n<1K
DOI:
License:
Dataset card Files
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  1. train/.bidsignore +6 -0
  2. train/CHANGES +7 -0
  3. train/README +1 -0
  4. train/dataset_description.json +35 -0
  5. train/participants.json +55 -0
  6. train/participants.tsv +81 -0
  7. train/sub-026/ses-vida/anat/sub-026_ses-vida_task-breathhold_acq-DIXONbodyIN_T1w.json +87 -0
  8. train/sub-026/ses-vida/anat/sub-026_ses-vida_task-breathhold_acq-DIXONbodyIN_chunk-0_T1w.json +97 -0
  9. train/sub-026/ses-vida/anat/sub-026_ses-vida_task-breathhold_acq-DIXONbodyIN_chunk-1_T1w.json +87 -0
  10. train/sub-026/ses-vida/anat/sub-026_ses-vida_task-breathhold_acq-DIXONbodyIN_chunk-2_T1w.json +87 -0
  11. train/sub-026/ses-vida/anat/sub-026_ses-vida_task-breathhold_acq-DIXONbodyIN_chunk-3_T1w.json +87 -0
  12. train/sub-026/ses-vida/anat/sub-026_ses-vida_task-breathhold_acq-DIXONbodyOUT_T1w.json +87 -0
  13. train/sub-026/ses-vida/anat/sub-026_ses-vida_task-breathhold_acq-DIXONbodyOUT_chunk-0_T1w.json +98 -0
  14. train/sub-026/ses-vida/anat/sub-026_ses-vida_task-breathhold_acq-DIXONbodyOUT_chunk-1_T1w.json +88 -0
  15. train/sub-026/ses-vida/anat/sub-026_ses-vida_task-breathhold_acq-DIXONbodyOUT_chunk-2_T1w.json +88 -0
  16. train/sub-026/ses-vida/anat/sub-026_ses-vida_task-breathhold_acq-DIXONbodyOUT_chunk-3_T1w.json +88 -0
  17. train/sub-026/ses-vida/anat/sub-026_ses-vida_task-breathhold_acq-DIXONbodyW_chunk-0_T1w.json +95 -0
  18. train/sub-026/ses-vida/anat/sub-026_ses-vida_task-breathhold_acq-DIXONbodyW_chunk-1_T1w.json +85 -0
  19. train/sub-026/ses-vida/anat/sub-026_ses-vida_task-breathhold_acq-DIXONheadIN_T1w.json +95 -0
  20. train/sub-026/ses-vida/anat/sub-026_ses-vida_task-breathhold_acq-DIXONheadOUT_T1w.json +96 -0
  21. train/sub-026/ses-vida/anat/sub-026_ses-vida_task-rest_acq-FASTVIEW_T1w.json +70 -0
  22. train/sub-026/ses-vida/anat/sub-026_ses-vida_task-rest_acq-MPRAGE_T1w.json +88 -0
  23. train/sub-069/ses-quadra/ct/sub-069_ses-quadra_acq-LOWDOSE_ce-none_rec-ac_ct.json +1132 -0
  24. train/sub-069/ses-quadra/ct/sub-069_ses-quadra_acq-LOWDOSE_ce-none_rec-br38f_ct.json +1144 -0
  25. train/sub-069/ses-quadra/ct/sub-069_ses-quadra_acq-TOPOGRAM_ce-none_rec-tr20f_Xray.json +34 -0
  26. train/sub-069/ses-quadra/pet/sub-069_ses-quadra_trc-18FFDG_rec-acdynPSF_pet.json +280 -0
  27. train/sub-069/ses-quadra/pet/sub-069_ses-quadra_trc-18FFDG_rec-acstatOSEM_pet.json +79 -0
  28. train/sub-069/ses-quadra/pet/sub-069_ses-quadra_trc-18FFDG_rec-acstatOSEMhead_pet.json +79 -0
  29. train/sub-069/ses-quadra/pet/sub-069_ses-quadra_trc-18FFDG_rec-acstatPSF_pet.json +79 -0
  30. train/sub-069/ses-quadra/pet/sub-069_ses-quadra_trc-18FFDG_rec-nacstatOSEM_pet.json +76 -0
  31. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-breathhold_acq-DIXONbodyIN_T1w.json +87 -0
  32. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-breathhold_acq-DIXONbodyIN_chunk-0_T1w.json +97 -0
  33. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-breathhold_acq-DIXONbodyIN_chunk-1_T1w.json +87 -0
  34. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-breathhold_acq-DIXONbodyIN_chunk-2_T1w.json +87 -0
  35. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-breathhold_acq-DIXONbodyIN_chunk-3_T1w.json +87 -0
  36. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-breathhold_acq-DIXONbodyOUT_T1w.json +87 -0
  37. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-breathhold_acq-DIXONbodyOUT_chunk-0_T1w.json +98 -0
  38. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-breathhold_acq-DIXONbodyOUT_chunk-1_T1w.json +88 -0
  39. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-breathhold_acq-DIXONbodyOUT_chunk-2_T1w.json +88 -0
  40. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-breathhold_acq-DIXONbodyOUT_chunk-3_T1w.json +88 -0
  41. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-breathhold_acq-DIXONbodyW_T1w.json +84 -0
  42. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-breathhold_acq-DIXONbodyW_chunk-0_T1w.json +95 -0
  43. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-breathhold_acq-DIXONbodyW_chunk-1_T1w.json +85 -0
  44. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-breathhold_acq-DIXONbodyW_chunk-2_T1w.json +85 -0
  45. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-breathhold_acq-DIXONbodyW_chunk-3_T1w.json +85 -0
  46. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-breathhold_acq-DIXONheadIN_T1w.json +95 -0
  47. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-breathhold_acq-DIXONheadOUT_T1w.json +96 -0
  48. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-breathhold_acq-DIXONheadW_T1w.json +93 -0
  49. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-rest_acq-FASTVIEW_T1w.json +70 -0
  50. train/sub-069/ses-vida/anat/sub-069_ses-vida_task-rest_acq-MPRAGE_T1w.json +88 -0
train/.bidsignore ADDED
@@ -0,0 +1,6 @@
 
 
 
 
 
 
 
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+ tmp_dcm2bids
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+ *_ct.nii.gz
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+ *_ct.json
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+ *_Xray.json
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+ *_Xray.nii.gz
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+ */ct/*
train/CHANGES ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ Revision history for your dataset
2
+
3
+ 1.0.0 2025-05-10
4
+ - Initialized study directory
5
+
6
+ 1.1.0 2026-03-31
7
+ - Anatomical images have been defaced
train/README ADDED
@@ -0,0 +1 @@
 
 
1
+ hedyPET-100
train/dataset_description.json ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
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+ "Name": "hedyPET",
3
+ "BIDSVersion": "v1.1.0",
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+ "License": "DUA",
5
+ "DatasetType":"raw",
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+ "Authors": [
7
+ "Christian Hinge",
8
+ "Frederikke Engel Høi-Hansen",
9
+ "Rasmus Hvass Hansen",
10
+ "Kirsten Korsholm",
11
+ "Helle Hjorth Johannesen",
12
+ "Elisabeth Albrech-Beste",
13
+ "Eunice Sánchez Saxtoft",
14
+ "Vibeke Jensen",
15
+ "Christina Schulze",
16
+ "Christina Mikkelsen",
17
+ "Cyril Pernet",
18
+ "Janna Nissen",
19
+ "Zuzanna Czelusniak",
20
+ "Thomas Lund Andersen",
21
+ "Sisse Rye Ostrowski",
22
+ "Barbara Malene Fischer",
23
+ "Claes Nøhr Ladefoged",
24
+ "Flemming Littrup Andersen"
25
+ ],
26
+ "HowToAcknowledge": "Please cite this paper x",
27
+ "ReferencesAndLinks": [
28
+ "http://github.com/depict-rh/hedyPET"
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+ ],
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+ "DatasetDOI": "XXXX",
31
+ "EthicsApprovals": [
32
+ "Healthy Digital Twin (HEDIT Study): Towards a Synthetic Baseline PET for Precision Medicine (Journal Number H-23065644). Prior to obtaining participation consent, each participant was informed verbally and in writing of the intended data sharing and its scope. Each participant has consented to the data sharing."
33
+ ]
34
+ }
35
+
train/participants.json ADDED
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+ {
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+ "sex": {
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+ "Description": "sex of the participant as reported by the participant",
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+ "Levels": {
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+ "M": "male",
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+ "F": "female"
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+ }
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+ },
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+ "age": {
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+ "Description": "age of the participant",
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+ "Units": "year"
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+ },
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+ "weight": {
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+ "Description": "measured weight of the participant",
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+ "Units": "kilogram"
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+ },
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+ "height":{
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+ "Description": "reported height of the participant",
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+ "Units": "meter"
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+ },
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+ "demographic-group": {
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+ "Description": "demographic group the participant",
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+ "Levels": {
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+ "F18-34": "female participants age 18-34",
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+ "F35-49": "female participants age 35-49",
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+ "F50-69": "female participants age 50-69",
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+ "F70-99": "female participants age 70-99",
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+ "M18-34": "male participants age 18-34",
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+ "M35-49": "male participants age 35-49",
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+ "M50-69": "male participants age 50-69",
31
+ "M70-99": "male participants age 70-99"
32
+ }
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+ },
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+ "blanket": {
35
+ "Description": "whether a cushioning blanket was used during PET/CT to reduces ischemic PET artefacts",
36
+ "Levels":{
37
+ "YES": "yes",
38
+ "NO": "no"
39
+ }
40
+ },
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+ "suv_const":{
42
+ "Description": "The Standard Uptake Value (SUV) normalization constant. The PET image can be SUV normalized by dividing the voxel intensities by this constant: SUV=PET/suv_const",
43
+ "Units": "Bq/mL"
44
+ },
45
+ "sul_james_const":{
46
+ "Description": "Lean Body Mass Standard Uptake Value (SUL) constant calculated using the James lean body mass equation. The PET image can be SUL normalized by dividing the voxel intensities by this constant: SUL_james=PET/sul_james_const",
47
+ "Units": "Bq/mL"
48
+ },
49
+ "sul_janma_const":{
50
+ "Description": "Lean Body Mass Standard Uptake Value (SUL) constant calculated using the Janmahasatian lean body mass equation. The PET image can be SUL normalized by dividing the voxel intensities by this constant: SUL_janma=PET/sul_janma_const",
51
+ "Units": "Bq/mL"
52
+ }
53
+
54
+
55
+ }
train/participants.tsv ADDED
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+ participant_id sex age height weight demographic-group blanket suv_const sul_janma_const sul_james_const
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+ sub-000 M 28 1.84 83 M18-34 NO 422.99499334249583 546.4423915541344 538.0244084591975
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train/sub-026/ses-vida/anat/sub-026_ses-vida_task-breathhold_acq-DIXONbodyIN_T1w.json ADDED
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+ {
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+ "AcquisitionMatrixPE": 234,
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+ "BaseResolution": 384,
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+ "BodyPart": "WHOLEBODY",
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+ "CoilCombinationMethod": "Adaptive Combine",
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+ "CoilString": "1",
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