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Datasets:
DEPICT-RH
/
Multimodal-HC

Tasks:
Any-to-Any
Image-to-Image
Image Segmentation
Size:
n<1K
DOI:
License:
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  1. train/derivatives/niftidynamic/README +13 -0
  2. train/derivatives/niftidynamic/dataset_description.json +21 -0
  3. train/derivatives/niftidynamic/dseg.tsv +5 -0
  4. train/derivatives/niftidynamic/participants.json +55 -0
  5. train/derivatives/niftidynamic/participants.tsv +81 -0
  6. train/derivatives/niftidynamic/sub-000/sub-000_seg-aortasegments_dseg.json +8 -0
  7. train/derivatives/niftidynamic/sub-000/sub-000_seg-aortavois_ml-1_width-3_dseg.json +8 -0
  8. train/derivatives/niftidynamic/sub-000/sub-000_seg-aortavois_ml-2_width-5_dseg.json +8 -0
  9. train/derivatives/niftidynamic/sub-000/sub-000_seg-aortavois_ml-full_width-3_dseg.json +8 -0
  10. train/derivatives/niftidynamic/sub-001/sub-001_seg-aortasegments_dseg.json +8 -0
  11. train/derivatives/niftidynamic/sub-001/sub-001_seg-aortavois_ml-1_width-3_dseg.json +8 -0
  12. train/derivatives/niftidynamic/sub-001/sub-001_seg-aortavois_ml-2_width-5_dseg.json +8 -0
  13. train/derivatives/niftidynamic/sub-001/sub-001_seg-aortavois_ml-full_width-3_dseg.json +8 -0
  14. train/derivatives/niftidynamic/sub-002/sub-002_seg-aortasegments_dseg.json +8 -0
  15. train/derivatives/niftidynamic/sub-002/sub-002_seg-aortavois_ml-1_width-3_dseg.json +8 -0
  16. train/derivatives/niftidynamic/sub-002/sub-002_seg-aortavois_ml-2_width-5_dseg.json +8 -0
  17. train/derivatives/niftidynamic/sub-002/sub-002_seg-aortavois_ml-full_width-3_dseg.json +8 -0
  18. train/derivatives/niftidynamic/sub-004/sub-004_seg-aortasegments_dseg.json +8 -0
  19. train/derivatives/niftidynamic/sub-004/sub-004_seg-aortavois_ml-1_width-3_dseg.json +8 -0
  20. train/derivatives/niftidynamic/sub-004/sub-004_seg-aortavois_ml-2_width-5_dseg.json +8 -0
  21. train/derivatives/niftidynamic/sub-004/sub-004_seg-aortavois_ml-full_width-3_dseg.json +8 -0
  22. train/derivatives/niftidynamic/sub-005/sub-005_seg-aortasegments_dseg.json +8 -0
  23. train/derivatives/niftidynamic/sub-005/sub-005_seg-aortavois_ml-1_width-3_dseg.json +8 -0
  24. train/derivatives/niftidynamic/sub-005/sub-005_seg-aortavois_ml-2_width-5_dseg.json +8 -0
  25. train/derivatives/niftidynamic/sub-005/sub-005_seg-aortavois_ml-full_width-3_dseg.json +8 -0
  26. train/derivatives/niftidynamic/sub-006/sub-006_seg-aortasegments_dseg.json +8 -0
  27. train/derivatives/niftidynamic/sub-006/sub-006_seg-aortavois_ml-1_width-3_dseg.json +8 -0
  28. train/derivatives/niftidynamic/sub-006/sub-006_seg-aortavois_ml-2_width-5_dseg.json +8 -0
  29. train/derivatives/niftidynamic/sub-006/sub-006_seg-aortavois_ml-full_width-3_dseg.json +8 -0
  30. train/derivatives/niftidynamic/sub-008/sub-008_seg-aortasegments_dseg.json +8 -0
  31. train/derivatives/niftidynamic/sub-008/sub-008_seg-aortavois_ml-1_width-3_dseg.json +8 -0
  32. train/derivatives/niftidynamic/sub-008/sub-008_seg-aortavois_ml-2_width-5_dseg.json +8 -0
  33. train/derivatives/niftidynamic/sub-008/sub-008_seg-aortavois_ml-full_width-3_dseg.json +8 -0
  34. train/derivatives/niftidynamic/sub-009/sub-009_seg-aortasegments_dseg.json +8 -0
  35. train/derivatives/niftidynamic/sub-009/sub-009_seg-aortavois_ml-1_width-3_dseg.json +8 -0
  36. train/derivatives/niftidynamic/sub-009/sub-009_seg-aortavois_ml-2_width-5_dseg.json +8 -0
  37. train/derivatives/niftidynamic/sub-009/sub-009_seg-aortavois_ml-full_width-3_dseg.json +8 -0
  38. train/derivatives/niftidynamic/sub-010/sub-010_seg-aortasegments_dseg.json +8 -0
  39. train/derivatives/niftidynamic/sub-010/sub-010_seg-aortavois_ml-1_width-3_dseg.json +8 -0
  40. train/derivatives/niftidynamic/sub-010/sub-010_seg-aortavois_ml-2_width-5_dseg.json +8 -0
  41. train/derivatives/niftidynamic/sub-010/sub-010_seg-aortavois_ml-full_width-3_dseg.json +8 -0
  42. train/derivatives/niftidynamic/sub-013/sub-013_seg-aortasegments_dseg.json +8 -0
  43. train/derivatives/niftidynamic/sub-013/sub-013_seg-aortavois_ml-1_width-3_dseg.json +8 -0
  44. train/derivatives/niftidynamic/sub-013/sub-013_seg-aortavois_ml-2_width-5_dseg.json +8 -0
  45. train/derivatives/niftidynamic/sub-013/sub-013_seg-aortavois_ml-full_width-3_dseg.json +8 -0
  46. train/derivatives/niftidynamic/sub-014/sub-014_seg-aortasegments_dseg.json +8 -0
  47. train/derivatives/niftidynamic/sub-014/sub-014_seg-aortavois_ml-1_width-3_dseg.json +8 -0
  48. train/derivatives/niftidynamic/sub-014/sub-014_seg-aortavois_ml-2_width-5_dseg.json +8 -0
  49. train/derivatives/niftidynamic/sub-014/sub-014_seg-aortavois_ml-full_width-3_dseg.json +8 -0
  50. train/derivatives/niftidynamic/sub-015/sub-015_seg-aortasegments_dseg.json +8 -0
train/derivatives/niftidynamic/README ADDED
@@ -0,0 +1,13 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Extraction of aorta segments and volumes of interest (VOIs) from CT and PET data.
2
+ The python library nifti_dynamic is used along with the the totalsegmentator aorta segmentation to:
3
+ 1. crop errode the aorta mask to match areas of PET activity
4
+ 2. segment the aorta into four chunks: ascending, top, descending_upper, and descending_lower
5
+ 3. define cylindric volumes of interest (of fixed volume and width) from the centerline of said segments
6
+
7
+ The voi extraction is run for the following three following settings:
8
+ - 1ml volume and 3px width
9
+ - 1.5ml volume 5px width
10
+ - 2ml volume 5px width
11
+
12
+ In each setting, a .jpg visualization is generated to show the VOIs overlaid ontop the PET MIP, and ontop the PET volume unrolled along the aortacenterline
13
+
train/derivatives/niftidynamic/dataset_description.json ADDED
@@ -0,0 +1,21 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "Name": "niftidynamic",
3
+ "BIDSVersion": "v1.11.1",
4
+ "DatasetType":"derivative",
5
+ "GeneratedBy": [
6
+ {
7
+ "Name": "nifti_dynamic",
8
+ "Version": "0.3.1",
9
+ "Description": "Aorta volumes of interest (VOIs) extracted using nifti_dynamic. Aorta VOIs can be used for extracting PET input functions." ,
10
+ "CodeURL": "https://github.com/ChristianHinge/nifti_dynamic"
11
+ },
12
+ {
13
+ "Name": "multimodal-hc",
14
+ "Version": "1.0.0",
15
+ "CodeURL": "https://github.com/DEPICT-RH/Multimodal-HC"
16
+ }],
17
+ "DatasetLinks": {
18
+ "dynamic":"dynamic",
19
+ "pipeline-bodydyn": "dynamic/derivatives/pipeline-bodydyn"
20
+ }
21
+ }
train/derivatives/niftidynamic/dseg.tsv ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ index name
2
+ 1 ascending_aorta
3
+ 2 top_aorta
4
+ 3 upper_descending_aorta
5
+ 4 lower_descending_aorta
train/derivatives/niftidynamic/participants.json ADDED
@@ -0,0 +1,55 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "sex": {
3
+ "Description": "sex of the participant as reported by the participant",
4
+ "Levels": {
5
+ "M": "male",
6
+ "F": "female"
7
+ }
8
+ },
9
+ "age": {
10
+ "Description": "age of the participant",
11
+ "Units": "year"
12
+ },
13
+ "weight": {
14
+ "Description": "measured weight of the participant",
15
+ "Units": "kilogram"
16
+ },
17
+ "height":{
18
+ "Description": "reported height of the participant",
19
+ "Units": "meter"
20
+ },
21
+ "demographic-group": {
22
+ "Description": "demographic group the participant",
23
+ "Levels": {
24
+ "F18-34": "female participants age 18-34",
25
+ "F35-49": "female participants age 35-49",
26
+ "F50-69": "female participants age 50-69",
27
+ "F70-99": "female participants age 70-99",
28
+ "M18-34": "male participants age 18-34",
29
+ "M35-49": "male participants age 35-49",
30
+ "M50-69": "male participants age 50-69",
31
+ "M70-99": "male participants age 70-99"
32
+ }
33
+ },
34
+ "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
+ },
41
+ "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/derivatives/niftidynamic/participants.tsv ADDED
@@ -0,0 +1,81 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 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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+ sub-001 M 49 1.89 82 M35-49 YES 353.9410723924101 444.37083301021994 439.04174541635365
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+ sub-002 F 29 1.76 70 F18-34 NO 392.58824091342353 605.3543933296136 533.7360671959578
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+ sub-004 F 25 1.72 77 F18-34 YES 375.1532218323389 612.3346445351802 547.8354634949175
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+ sub-005 M 78 1.76 73 M70-99 YES 425.6579122099182 540.47041249461 533.1739894140796
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+ sub-006 F 72 1.65 110 F70-99 YES 422.9445078152545 850.3870034878057 896.0305215859231
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+ sub-008 M 57 1.78 95 M50-69 NO 357.7798064005185 507.77927943180856 499.545900213024
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+ sub-009 M 55 1.86 86 M50-69 NO 449.9509314218932 584.8588827690035 575.5225019399804
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+ sub-010 M 49 1.72 74 M35-49 YES 407.93417721997565 531.7191188337722 523.1086023162042
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+ sub-013 F 45 1.77 87 F35-49 NO 475.95037401370627 798.6842977081269 722.2235590801429
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+ sub-014 F 67 1.67 59 F50-69 YES 476.08825437781223 716.027068261476 628.9961939086743
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+ sub-015 M 34 1.8 72 M18-34 YES 423.34490512325755 524.271791889428 519.0877583255201
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+ sub-018 F 77 1.69 67 F70-99 YES 434.55428957811404 679.9058550083925 601.1985439369141
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+ sub-019 M 73 1.73 74 M70-99 YES 378.2647495282709 490.5053068769697 482.777567863045
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+ sub-020 M 37 1.9 113 M35-49 YES 390.8330653193792 566.6960905634646 558.8637272450917
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+ sub-021 M 67 1.79 72 M50-69 NO 394.66326430728117 491.04203839902556 485.81801336464173
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+ sub-022 M 76 1.76 75 M70-99 YES 413.9260047328155 531.801386303837 523.9021608019945
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+ sub-024 F 73 1.655 63 F70-99 YES 371.17937449541586 576.277642076622 508.7527971305955
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+ sub-025 F 26 1.69 102 F18-34 NO 430.6959615658735 812.792534777713 795.4534781326835
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+ sub-027 F 74 1.7 68 F70-99 YES 390.62851467686 611.9078312908792 541.2131010192844
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+ sub-028 F 53 1.71 67 F50-69 YES 426.1289540516107 660.6046903714408 583.0297837963242
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+ sub-029 M 25 1.93 85 M18-34 YES 369.39869214177463 462.6047717059079 457.2266101631547
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+ sub-030 M 45 1.74 79 M35-49 YES 408.0974265445065 542.1993610186688 532.7600375162334
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+ sub-032 F 38 1.7 72 F35-49 YES 400.1668791504333 641.4279107682161 570.6233190628865
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+ sub-098 M 24 1.865 93 M18-34 NO 331.4071974524754 445.2854158048259 437.35317388199144
train/derivatives/niftidynamic/sub-000/sub-000_seg-aortasegments_dseg.json ADDED
@@ -0,0 +1,8 @@
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "Description": "Aorta segments nifty_dynamic v0.3.1",
3
+ "Sources": [
4
+ "bids:raw:sub-000/ses-quadra/pet/sub-000_ses-quadra_trc-18FFDG_rec-acdynPSF_pet.nii.gz",
5
+ "bids:pipeline-bodydyn:sub-000/ses-quadra/ct/sub-000_ses-quadra_acq-LOWDOSE_ce-none_rec-br38f_seg-total_space-individual_dseg.nii.gz"
6
+ ],
7
+ "SpatialReference": "bids:raw:sub-000/ses-quadra/pet/sub-000_ses-quadra_trc-18FFDG_rec-acdynPSF_pet.nii.gz"
8
+ }
train/derivatives/niftidynamic/sub-000/sub-000_seg-aortavois_ml-1_width-3_dseg.json ADDED
@@ -0,0 +1,8 @@
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "Description": "Aorta vois nifty_dynamic v0.3.1, volume: 1ml, cylinder width: 3pixels.",
3
+ "Sources": [
4
+ "bids:raw:sub-000/ses-quadra/pet/sub-000_ses-quadra_trc-18FFDG_rec-acdynPSF_pet.nii.gz",
5
+ "bids:pipeline-bodydyn:sub-000/ses-quadra/ct/sub-000_ses-quadra_acq-LOWDOSE_ce-none_rec-br38f_seg-total_space-individual_dseg.nii.gz"
6
+ ],
7
+ "SpatialReference": "bids:raw:sub-000/ses-quadra/pet/sub-000_ses-quadra_trc-18FFDG_rec-acdynPSF_pet.nii.gz"
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+ }
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