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The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
cases_dir: string
organ_set: string
spacing_mm: double
n_cases: int64
n_accepted: int64
n_rejected: int64
rejection_reasons: struct<all targets below minimum volume: int64, body truncated by FOV: int64, no target has a reacha (... 19 chars omitted)
child 0, all targets below minimum volume: int64
child 1, body truncated by FOV: int64
child 2, no target has a reachable surface: int64
accepted: list<item: struct<pid: string, ok: bool, targets: list<item: string>, n_surface_points: int64, heigh (... 74 chars omitted)
child 0, item: struct<pid: string, ok: bool, targets: list<item: string>, n_surface_points: int64, heightmap_valid_ (... 62 chars omitted)
child 0, pid: string
child 1, ok: bool
child 2, targets: list<item: string>
child 0, item: string
child 3, n_surface_points: int64
child 4, heightmap_valid_fraction: double
child 5, n_structures: int64
child 6, fov_truncation: double
rejected: list<item: struct<pid: string, reason: string>>
child 0, item: struct<pid: string, reason: string>
child 0, pid: string
child 1, reason: string
pid: string
targets: struct<vertebrae_L1: struct<name: string, label_id: int64, centroid_mm: list<item: double>, volume_m (... 436 chars omitted)
child 0, vertebrae_L1: struct<name: string, label_id: int64, centroid_mm: list<item: double>, volume_mm3: double>
child 0, name: string
child 1, label_id: int64
child 2, centroid_mm: list<item: double>
c
...
tem: double>>
child 0, item: list<item: double>
child 0, item: double
qc: struct<pid: string, ok: bool, reason: null, targets_present: list<item: string>, target_volumes_mm3: (... 451 chars omitted)
child 0, pid: string
child 1, ok: bool
child 2, reason: null
child 3, targets_present: list<item: string>
child 0, item: string
child 4, target_volumes_mm3: struct<vertebrae_L1: double, vertebrae_L2: double, vertebrae_L3: double, vertebrae_L4: double, verte (... 16 chars omitted)
child 0, vertebrae_L1: double
child 1, vertebrae_L2: double
child 2, vertebrae_L3: double
child 3, vertebrae_L4: double
child 4, vertebrae_L5: double
child 5, fov_truncation: double
child 6, spacing_mm: list<item: double>
child 0, item: double
child 7, shape: list<item: int64>
child 0, item: int64
child 8, n_structures: int64
child 9, heightmap_source: string
child 10, heightmap_valid_fraction: double
child 11, target_reachable_fraction: struct<vertebrae_L1: double, vertebrae_L2: double, vertebrae_L3: double, vertebrae_L4: double, verte (... 16 chars omitted)
child 0, vertebrae_L1: double
child 1, vertebrae_L2: double
child 2, vertebrae_L3: double
child 3, vertebrae_L4: double
child 4, vertebrae_L5: double
child 12, n_surface_points: int64
affine: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
shape: list<item: int64>
child 0, item: int64
to
{'pid': Value('string'), 'organ_set': Value('string'), 'affine': List(List(Value('float64'))), 'shape': List(Value('int64')), 'targets': {'vertebrae_L1': {'name': Value('string'), 'label_id': Value('int64'), 'centroid_mm': List(Value('float64')), 'volume_mm3': Value('float64')}, 'vertebrae_L2': {'name': Value('string'), 'label_id': Value('int64'), 'centroid_mm': List(Value('float64')), 'volume_mm3': Value('float64')}, 'vertebrae_L3': {'name': Value('string'), 'label_id': Value('int64'), 'centroid_mm': List(Value('float64')), 'volume_mm3': Value('float64')}, 'vertebrae_L4': {'name': Value('string'), 'label_id': Value('int64'), 'centroid_mm': List(Value('float64')), 'volume_mm3': Value('float64')}, 'vertebrae_L5': {'name': Value('string'), 'label_id': Value('int64'), 'centroid_mm': List(Value('float64')), 'volume_mm3': Value('float64')}}, 'frame': {'A': List(List(Value('float64')))}, 'qc': {'pid': Value('string'), 'ok': Value('bool'), 'reason': Value('null'), 'targets_present': List(Value('string')), 'target_volumes_mm3': {'vertebrae_L1': Value('float64'), 'vertebrae_L2': Value('float64'), 'vertebrae_L3': Value('float64'), 'vertebrae_L4': Value('float64'), 'vertebrae_L5': Value('float64')}, 'fov_truncation': Value('float64'), 'spacing_mm': List(Value('float64')), 'shape': List(Value('int64')), 'n_structures': Value('int64'), 'heightmap_source': Value('string'), 'heightmap_valid_fraction': Value('float64'), 'target_reachable_fraction': {'vertebrae_L1': Value('float64'), 'vertebrae_L2': Value('float64'), 'vertebrae_L3': Value('float64'), 'vertebrae_L4': Value('float64'), 'vertebrae_L5': Value('float64')}, 'n_surface_points': Value('int64')}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
cases_dir: string
organ_set: string
spacing_mm: double
n_cases: int64
n_accepted: int64
n_rejected: int64
rejection_reasons: struct<all targets below minimum volume: int64, body truncated by FOV: int64, no target has a reacha (... 19 chars omitted)
child 0, all targets below minimum volume: int64
child 1, body truncated by FOV: int64
child 2, no target has a reachable surface: int64
accepted: list<item: struct<pid: string, ok: bool, targets: list<item: string>, n_surface_points: int64, heigh (... 74 chars omitted)
child 0, item: struct<pid: string, ok: bool, targets: list<item: string>, n_surface_points: int64, heightmap_valid_ (... 62 chars omitted)
child 0, pid: string
child 1, ok: bool
child 2, targets: list<item: string>
child 0, item: string
child 3, n_surface_points: int64
child 4, heightmap_valid_fraction: double
child 5, n_structures: int64
child 6, fov_truncation: double
rejected: list<item: struct<pid: string, reason: string>>
child 0, item: struct<pid: string, reason: string>
child 0, pid: string
child 1, reason: string
pid: string
targets: struct<vertebrae_L1: struct<name: string, label_id: int64, centroid_mm: list<item: double>, volume_m (... 436 chars omitted)
child 0, vertebrae_L1: struct<name: string, label_id: int64, centroid_mm: list<item: double>, volume_mm3: double>
child 0, name: string
child 1, label_id: int64
child 2, centroid_mm: list<item: double>
c
...
tem: double>>
child 0, item: list<item: double>
child 0, item: double
qc: struct<pid: string, ok: bool, reason: null, targets_present: list<item: string>, target_volumes_mm3: (... 451 chars omitted)
child 0, pid: string
child 1, ok: bool
child 2, reason: null
child 3, targets_present: list<item: string>
child 0, item: string
child 4, target_volumes_mm3: struct<vertebrae_L1: double, vertebrae_L2: double, vertebrae_L3: double, vertebrae_L4: double, verte (... 16 chars omitted)
child 0, vertebrae_L1: double
child 1, vertebrae_L2: double
child 2, vertebrae_L3: double
child 3, vertebrae_L4: double
child 4, vertebrae_L5: double
child 5, fov_truncation: double
child 6, spacing_mm: list<item: double>
child 0, item: double
child 7, shape: list<item: int64>
child 0, item: int64
child 8, n_structures: int64
child 9, heightmap_source: string
child 10, heightmap_valid_fraction: double
child 11, target_reachable_fraction: struct<vertebrae_L1: double, vertebrae_L2: double, vertebrae_L3: double, vertebrae_L4: double, verte (... 16 chars omitted)
child 0, vertebrae_L1: double
child 1, vertebrae_L2: double
child 2, vertebrae_L3: double
child 3, vertebrae_L4: double
child 4, vertebrae_L5: double
child 12, n_surface_points: int64
affine: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
shape: list<item: int64>
child 0, item: int64
to
{'pid': Value('string'), 'organ_set': Value('string'), 'affine': List(List(Value('float64'))), 'shape': List(Value('int64')), 'targets': {'vertebrae_L1': {'name': Value('string'), 'label_id': Value('int64'), 'centroid_mm': List(Value('float64')), 'volume_mm3': Value('float64')}, 'vertebrae_L2': {'name': Value('string'), 'label_id': Value('int64'), 'centroid_mm': List(Value('float64')), 'volume_mm3': Value('float64')}, 'vertebrae_L3': {'name': Value('string'), 'label_id': Value('int64'), 'centroid_mm': List(Value('float64')), 'volume_mm3': Value('float64')}, 'vertebrae_L4': {'name': Value('string'), 'label_id': Value('int64'), 'centroid_mm': List(Value('float64')), 'volume_mm3': Value('float64')}, 'vertebrae_L5': {'name': Value('string'), 'label_id': Value('int64'), 'centroid_mm': List(Value('float64')), 'volume_mm3': Value('float64')}}, 'frame': {'A': List(List(Value('float64')))}, 'qc': {'pid': Value('string'), 'ok': Value('bool'), 'reason': Value('null'), 'targets_present': List(Value('string')), 'target_volumes_mm3': {'vertebrae_L1': Value('float64'), 'vertebrae_L2': Value('float64'), 'vertebrae_L3': Value('float64'), 'vertebrae_L4': Value('float64'), 'vertebrae_L5': Value('float64')}, 'fov_truncation': Value('float64'), 'spacing_mm': List(Value('float64')), 'shape': List(Value('int64')), 'n_structures': Value('int64'), 'heightmap_source': Value('string'), 'heightmap_valid_fraction': Value('float64'), 'target_reachable_fraction': {'vertebrae_L1': Value('float64'), 'vertebrae_L2': Value('float64'), 'vertebrae_L3': Value('float64'), 'vertebrae_L4': Value('float64'), 'vertebrae_L5': Value('float64')}, 'n_surface_points': Value('int64')}}
because column names don't match
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
pid string | organ_set string | affine list | shape list | targets dict | frame dict | qc dict |
|---|---|---|---|---|---|---|
s0004 | spine | [
[
1.4974846839904785,
-0.052209723740816116,
0.0696103423833847,
-162.55699157714844
],
[
0.05155886337161064,
1.4990791082382202,
0.008581877686083317,
13.123804092407227
],
[
-0.06986502557992935,
-0.006001117639243603,
1.4983593225479126,
-11.58482170104980... | [
255,
177,
440
] | {
"vertebrae_L1": {
"name": "vertebrae_L1",
"label_id": 31,
"centroid_mm": [
24.184213850763626,
95.75511299448996,
321.68701404606634
],
"volume_mm3": 47412
},
"vertebrae_L2": {
"name": "vertebrae_L2",
"label_id": 30,
"centroid_mm": [
20.888916425047427,
... | {
"A": [
[
0.0030766995712342812,
0,
0,
0.4178638718530444
],
[
0,
0.004286244303031829,
0,
-0.13800653220342965
],
[
0,
0,
0.0016574212350435012,
-0.008632823754586879
],
[
0,
0,
0,
1
]
]... | {
"pid": "s0004",
"ok": true,
"reason": null,
"targets_present": [
"vertebrae_L1",
"vertebrae_L2",
"vertebrae_L3",
"vertebrae_L4",
"vertebrae_L5"
],
"target_volumes_mm3": {
"vertebrae_L1": 47415.37253711284,
"vertebrae_L2": 53547.74721858013,
"vertebrae_L3": 59268.37192143487... |
s0006 | spine | [
[
1.5,
0,
0,
-157.68359375
],
[
0,
1.5,
0,
-0.18359375
],
[
0,
0,
1.5,
-869
],
[
0,
0,
0,
1
]
] | [
216,
216,
217
] | {
"vertebrae_L1": {
"name": "vertebrae_L1",
"label_id": 31,
"centroid_mm": [
-2.0013841043307252,
101.93992987204723,
-555.060408464567
],
"volume_mm3": 41148
},
"vertebrae_L2": {
"name": "vertebrae_L2",
"label_id": 30,
"centroid_mm": [
-1.1303573292161673,
... | {
"A": [
[
0.003236245954692557,
0,
0,
0.4908854166666667
],
[
0,
0.00408997955010225,
0,
-0.13421843047034765
],
[
0,
0,
0.0031446540880503146,
2.7232704402515724
],
[
0,
0,
0,
1
]
]
} | {
"pid": "s0006",
"ok": true,
"reason": null,
"targets_present": [
"vertebrae_L1",
"vertebrae_L2",
"vertebrae_L3",
"vertebrae_L4",
"vertebrae_L5"
],
"target_volumes_mm3": {
"vertebrae_L1": 41148,
"vertebrae_L2": 68745.375,
"vertebrae_L3": 75427.875,
"vertebrae_L4": 75961.... |
s0010 | spine | [
[
1.5,
0,
0,
-195.1201171875
],
[
0,
1.5,
0,
-40.1201171875
],
[
0,
0,
1.5,
130.3000030517578
],
[
0,
0,
0,
1
]
] | [
259,
259,
283
] | {
"vertebrae_L1": {
"name": "vertebrae_L1",
"label_id": 31,
"centroid_mm": [
-6.244090550430087,
83.8312701598918,
434.2298587676291
],
"volume_mm3": 45613.125
},
"vertebrae_L2": {
"name": "vertebrae_L2",
"label_id": 30,
"centroid_mm": [
-5.737730538979122,
... | {
"A": [
[
0.0031007751937984496,
0,
0,
0.512000363372093
],
[
0,
0.0040650406504065045,
0,
-0.09910521468495935
],
[
0,
0,
0.0024067388688327317,
-0.3244284068634364
],
[
0,
0,
0,
1
]
]
} | {
"pid": "s0010",
"ok": true,
"reason": null,
"targets_present": [
"vertebrae_L1",
"vertebrae_L2",
"vertebrae_L3",
"vertebrae_L4",
"vertebrae_L5"
],
"target_volumes_mm3": {
"vertebrae_L1": 45613.125,
"vertebrae_L2": 47175.75,
"vertebrae_L3": 52214.625,
"vertebrae_L4": 522... |
s0011 | spine | [
[
1.5,
0,
0,
-236.544921875
],
[
0,
1.5,
0,
-45.544921875
],
[
0,
0,
1.5,
-61
],
[
0,
0,
0,
1
]
] | [
311,
311,
431
] | {
"vertebrae_L1": {
"name": "vertebrae_L1",
"label_id": 31,
"centroid_mm": [
-4.895746282269215,
117.16247372013783,
274.0901432181971
],
"volume_mm3": 56085.75
},
"vertebrae_L2": {
"name": "vertebrae_L2",
"label_id": 30,
"centroid_mm": [
-5.113748115173479,... | {
"A": [
[
0.002677376171352075,
0,
0,
0.5289020665997323
],
[
0,
0.003766478342749529,
0,
-0.1391905014124294
],
[
0,
0,
0.001579778830963665,
0.08688783570300158
],
[
0,
0,
0,
1
]
]
} | {
"pid": "s0011",
"ok": true,
"reason": null,
"targets_present": [
"vertebrae_L1",
"vertebrae_L2",
"vertebrae_L3",
"vertebrae_L4",
"vertebrae_L5"
],
"target_volumes_mm3": {
"vertebrae_L1": 56085.75,
"vertebrae_L2": 62268.75,
"vertebrae_L3": 68650.875,
"vertebrae_L4": 6655... |
s0014 | spine | [
[
1.5,
0,
0,
-214.0810546875
],
[
0,
1.5,
0,
-40.0810546875
],
[
0,
0,
1.5,
-206.1999969482422
],
[
0,
0,
0,
1
]
] | [
286,
286,
308
] | {
"vertebrae_L1": {
"name": "vertebrae_L1",
"label_id": 31,
"centroid_mm": [
13.575792729172605,
109.02871007690908,
108.65470421016875
],
"volume_mm3": 47489.625
},
"vertebrae_L2": {
"name": "vertebrae_L2",
"label_id": 30,
"centroid_mm": [
15.66632134166221... | {
"A": [
[
0.003236245954692557,
0,
0,
0.49864418992718446
],
[
0,
0.0034542314335060447,
0,
-0.08434868847150259
],
[
0,
0,
0.0022148394241417496,
0.4467331050902374
],
[
0,
0,
0,
1
]
]
} | {
"pid": "s0014",
"ok": true,
"reason": null,
"targets_present": [
"vertebrae_L1",
"vertebrae_L2",
"vertebrae_L3",
"vertebrae_L4",
"vertebrae_L5"
],
"target_volumes_mm3": {
"vertebrae_L1": 47489.625,
"vertebrae_L2": 53699.625,
"vertebrae_L3": 57233.25,
"vertebrae_L4": 563... |
s0015 | spine | [
[
1.5,
0,
0,
-225.0712890625
],
[
0,
1.5,
0,
-46.5712890625
],
[
0,
0,
1.5,
-146.5
],
[
0,
0,
0,
1
]
] | [
293,
293,
344
] | {
"vertebrae_L1": {
"name": "vertebrae_L1",
"label_id": 31,
"centroid_mm": [
-1.7058747547285122,
87.52641208692529,
197.1677817807514
],
"volume_mm3": 59018.625
},
"vertebrae_L2": {
"name": "vertebrae_L2",
"label_id": 30,
"centroid_mm": [
-1.276088935770644... | {
"A": [
[
0.0027662517289073307,
0,
0,
0.5188694026625172
],
[
0,
0.003898635477582846,
0,
-0.09913727461013645
],
[
0,
0,
0.001984126984126984,
0.2787698412698413
],
[
0,
0,
0,
1
]
]
} | {
"pid": "s0015",
"ok": true,
"reason": null,
"targets_present": [
"vertebrae_L1",
"vertebrae_L2",
"vertebrae_L3",
"vertebrae_L4",
"vertebrae_L5"
],
"target_volumes_mm3": {
"vertebrae_L1": 59018.625,
"vertebrae_L2": 63922.5,
"vertebrae_L3": 69990.75,
"vertebrae_L4": 72488... |
s0016 | spine | [
[
1.5,
0,
0,
-196.1201171875
],
[
0,
1.5,
0,
-33.1201171875
],
[
0,
0,
1.5,
-291.29998779296875
],
[
0,
0,
0,
1
]
] | [
259,
259,
294
] | {
"vertebrae_L1": {
"name": "vertebrae_L1",
"label_id": 31,
"centroid_mm": [
-7.156217608976988,
91.24555992446628,
65.93741370968837
],
"volume_mm3": 55252.125
},
"vertebrae_L2": {
"name": "vertebrae_L2",
"label_id": 30,
"centroid_mm": [
-9.96811143456523,
... | {
"A": [
[
0.003003003003003003,
0,
0,
0.5213817332957958
],
[
0,
0.003992015968063872,
0,
-0.09532887350299402
],
[
0,
0,
0.0023148148148148147,
0.6638888606318721
],
[
0,
0,
0,
1
]
]
} | {
"pid": "s0016",
"ok": true,
"reason": null,
"targets_present": [
"vertebrae_L1",
"vertebrae_L2",
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]
]
} | {
"pid": "s0291",
"ok": true,
"reason": null,
"targets_present": [
"vertebrae_L1",
"vertebrae_L2",
"vertebrae_L3",
"vertebrae_L4",
"vertebrae_L5"
],
"target_volumes_mm3": {
"vertebrae_L1": 36119.25,
"vertebrae_L2": 39200.625,
"vertebrae_L3": 43247.25,
"vertebrae_L4": 4574... |
s0293 | spine | [
[
1.5,
0,
0,
-186.6484375
],
[
0,
1.5,
0,
-27.6484375
],
[
0,
0,
1.5,
4.5
],
[
0,
0,
0,
1
]
] | [
240,
240,
329
] | {
"vertebrae_L1": {
"name": "vertebrae_L1",
"label_id": 31,
"centroid_mm": [
-3.5626085316556555,
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],
"volume_mm3": 59278.5
},
"vertebrae_L2": {
"name": "vertebrae_L2",
"label_id": 30,
"centroid_mm": [
-3.945576990036443,... | {
"A": [
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],
[
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[
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],
[
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0,
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]
]
} | {
"pid": "s0293",
"ok": true,
"reason": null,
"targets_present": [
"vertebrae_L1",
"vertebrae_L2",
"vertebrae_L3",
"vertebrae_L4",
"vertebrae_L5"
],
"target_volumes_mm3": {
"vertebrae_L1": 59278.5,
"vertebrae_L2": 63014.625,
"vertebrae_L3": 71519.625,
"vertebrae_L4": 7131... |
s0298 | spine | [
[
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0,
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],
[
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],
[
0,
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],
[
0,
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1
]
] | [
348,
206,
348
] | {
"vertebrae_L1": {
"name": "vertebrae_L1",
"label_id": 31,
"centroid_mm": [
-8.343090713708989,
108.85833581701007,
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],
"volume_mm3": 43308
},
"vertebrae_L2": {
"name": "vertebrae_L2",
"label_id": 30,
"centroid_mm": [
-11.414654332096404,
... | {
"A": [
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],
[
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]
]
} | {
"pid": "s0298",
"ok": true,
"reason": null,
"targets_present": [
"vertebrae_L1",
"vertebrae_L2",
"vertebrae_L3",
"vertebrae_L4",
"vertebrae_L5"
],
"target_volumes_mm3": {
"vertebrae_L1": 43696.12245387374,
"vertebrae_L2": 46895.62226744231,
"vertebrae_L3": 42609.37251719749... |
s0300 | spine | [
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],
[
0,
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0,
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],
[
0,
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1.5,
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],
[
0,
0,
0,
1
]
] | [
325,
325,
278
] | {
"vertebrae_L1": {
"name": "vertebrae_L1",
"label_id": 31,
"centroid_mm": [
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101.6084872159091,
352.546022345803
],
"volume_mm3": 47520
},
"vertebrae_L2": {
"name": "vertebrae_L2",
"label_id": 30,
"centroid_mm": [
10.139511405109488,
... | {
"A": [
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],
[
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],
[
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]
... | {
"pid": "s0300",
"ok": true,
"reason": null,
"targets_present": [
"vertebrae_L1",
"vertebrae_L2",
"vertebrae_L3",
"vertebrae_L4",
"vertebrae_L5"
],
"target_volumes_mm3": {
"vertebrae_L1": 47540.25,
"vertebrae_L2": 57823.875,
"vertebrae_L3": 61198.875,
"vertebrae_L4": 602... |
s0304 | spine | [
[
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],
[
0,
1.5,
0,
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],
[
0,
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1.5,
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],
[
0,
0,
0,
1
]
] | [
234,
231,
231
] | {
"vertebrae_L1": {
"name": "vertebrae_L1",
"label_id": 31,
"centroid_mm": [
-13.351164331188272,
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375.2822183560924
],
"volume_mm3": 69079.5
},
"vertebrae_L2": {
"name": "vertebrae_L2",
"label_id": 30,
"centroid_mm": [
-11.130520177166972... | {
"A": [
[
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0,
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],
[
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],
[
0,
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-0.3223853232436472
],
[
0,
0,
0,
1
]
]
... | {
"pid": "s0304",
"ok": true,
"reason": null,
"targets_present": [
"vertebrae_L1",
"vertebrae_L2",
"vertebrae_L3",
"vertebrae_L4",
"vertebrae_L5"
],
"target_volumes_mm3": {
"vertebrae_L1": 69089.625,
"vertebrae_L2": 74601,
"vertebrae_L3": 80487,
"vertebrae_L4": 77007.375,... |
s0306 | spine | [
[
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0,
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],
[
0,
1.5,
0,
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],
[
0,
0,
1.5,
94.3017578125
],
[
0,
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0,
1
]
] | [
245,
202,
225
] | {
"vertebrae_L1": {
"name": "vertebrae_L1",
"label_id": 31,
"centroid_mm": [
-4.190859221942134,
112.3481204771025,
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],
"volume_mm3": 60267.375
},
"vertebrae_L2": {
"name": "vertebrae_L2",
"label_id": 30,
"centroid_mm": [
-3.293420848971095... | {
"A": [
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],
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],
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],
[
0,
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0,
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]
]
} | {
"pid": "s0306",
"ok": true,
"reason": null,
"targets_present": [
"vertebrae_L1",
"vertebrae_L2",
"vertebrae_L3",
"vertebrae_L4",
"vertebrae_L5"
],
"target_volumes_mm3": {
"vertebrae_L1": 60270.75,
"vertebrae_L2": 61968.375,
"vertebrae_L3": 67550.625,
"vertebrae_L4": 673... |
s0307 | spine | [
[
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0,
0,
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],
[
0,
1.5,
0,
-20.6484375
],
[
0,
0,
1.5,
-729
],
[
0,
0,
0,
1
]
] | [
240,
240,
287
] | {
"vertebrae_L1": {
"name": "vertebrae_L1",
"label_id": 31,
"centroid_mm": [
-2.9448369678197253,
93.14762935514717,
-400.3433394312323
],
"volume_mm3": 40587.75
},
"vertebrae_L2": {
"name": "vertebrae_L2",
"label_id": 30,
"centroid_mm": [
-1.966909619872268... | {
"A": [
[
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0,
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],
[
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],
[
0,
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1.7163120567375887
],
[
0,
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0,
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]
]
} | {
"pid": "s0307",
"ok": true,
"reason": null,
"targets_present": [
"vertebrae_L1",
"vertebrae_L2",
"vertebrae_L3",
"vertebrae_L4",
"vertebrae_L5"
],
"target_volumes_mm3": {
"vertebrae_L1": 40587.75,
"vertebrae_L2": 41218.875,
"vertebrae_L3": 47223,
"vertebrae_L4": 48799.1... |
s0311 | spine | [
[
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0,
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],
[
0.08132655918598175,
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0,
24.011510848999023
],
[
0,
0,
1.5,
71.82772827148438
],
[
0,
0,
0,
1
]
] | [
292,
164,
292
] | {
"vertebrae_L1": {
"name": "vertebrae_L1",
"label_id": 31,
"centroid_mm": [
5.587879123898773,
111.9973603984018,
388.6153249260528
],
"volume_mm3": 64162.125
},
"vertebrae_L2": {
"name": "vertebrae_L2",
"label_id": 30,
"centroid_mm": [
5.948941426555535,
... | {
"A": [
[
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0,
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0.47116051136484366
],
[
0,
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],
[
0,
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-0.18530411493210566
],
[
0,
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0,
1
]
]
} | {
"pid": "s0311",
"ok": true,
"reason": null,
"targets_present": [
"vertebrae_L1",
"vertebrae_L2",
"vertebrae_L3",
"vertebrae_L4",
"vertebrae_L5"
],
"target_volumes_mm3": {
"vertebrae_L1": 64162.13103094684,
"vertebrae_L2": 70088.63158801079,
"vertebrae_L3": 78489.00737760768... |
s0314 | spine | [
[
1.5,
0,
0,
-228.5625
],
[
0,
1.5,
0,
-63.5625
],
[
0,
0,
1.5,
27
],
[
0,
0,
0,
1
]
] | [
299,
299,
273
] | {
"vertebrae_L1": {
"name": "vertebrae_L1",
"label_id": 31,
"centroid_mm": [
2.6920822027797726,
87.18421908743562,
355.2847887479927
],
"volume_mm3": 60949.125
},
"vertebrae_L2": {
"name": "vertebrae_L2",
"label_id": 30,
"centroid_mm": [
3.0307034655330085,... | {
"A": [
[
0.0033003300330033004,
0,
0,
0.4969059405940594
],
[
0,
0.00516795865633075,
0,
-0.14437984496124032
],
[
0,
0,
0.0024875621890547263,
-0.07462686567164178
],
[
0,
0,
0,
1
]
]
} | {
"pid": "s0314",
"ok": true,
"reason": null,
"targets_present": [
"vertebrae_L1",
"vertebrae_L2",
"vertebrae_L3",
"vertebrae_L4",
"vertebrae_L5"
],
"target_volumes_mm3": {
"vertebrae_L1": 60949.125,
"vertebrae_L2": 62721,
"vertebrae_L3": 69528.375,
"vertebrae_L4": 72805.... |
s0319 | spine | [
[
1.4890233278274536,
0.13230396807193756,
0.123711958527565,
-234.61155700683594
],
[
-0.13250206410884857,
1.4941390752792358,
-0.004291564226150513,
15.22343635559082
],
[
-0.12350193411111832,
-0.00665964325889945,
1.49488365650177,
-184.13197326660156
]... | [
270,
213,
338
] | {
"vertebrae_L1": {
"name": "vertebrae_L1",
"label_id": 31,
"centroid_mm": [
-4.341303274260014,
133.52235687949792,
145.82653113597428
],
"volume_mm3": 65623.5
},
"vertebrae_L2": {
"name": "vertebrae_L2",
"label_id": 30,
"centroid_mm": [
-8.852411205611844,... | {
"A": [
[
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0,
0,
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],
[
0,
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],
[
0,
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0.0021036478306809127,
0.3875670292536238
],
[
0,
0,
0,
1
]
]
} | {
"pid": "s0319",
"ok": true,
"reason": null,
"targets_present": [
"vertebrae_L1",
"vertebrae_L2",
"vertebrae_L3",
"vertebrae_L4",
"vertebrae_L5"
],
"target_volumes_mm3": {
"vertebrae_L1": 65623.50693146286,
"vertebrae_L2": 74736.007893968,
"vertebrae_L3": 81641.258623333,
... |
s0320 | spine | [
[
1.5,
0,
0,
-213.6015625
],
[
0,
1.5,
0,
-12.6015625
],
[
0,
0,
1.5,
40.5
],
[
0,
0,
0,
1
]
] | [
272,
272,
282
] | {
"vertebrae_L1": {
"name": "vertebrae_L1",
"label_id": 31,
"centroid_mm": [
-9.347098963871957,
104.39423981712095,
384.32036715732914
],
"volume_mm3": 60301.125
},
"vertebrae_L2": {
"name": "vertebrae_L2",
"label_id": 30,
"centroid_mm": [
-9.57449251794412... | {
"A": [
[
0.0029498525073746312,
0,
0,
0.5548718657817109
],
[
0,
0.003745318352059925,
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],
[
0,
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0.0024154589371980675,
-0.10869565217391304
],
[
0,
0,
0,
1
]
]
} | {
"pid": "s0320",
"ok": true,
"reason": null,
"targets_present": [
"vertebrae_L1",
"vertebrae_L2",
"vertebrae_L3",
"vertebrae_L4",
"vertebrae_L5"
],
"target_volumes_mm3": {
"vertebrae_L1": 60301.125,
"vertebrae_L2": 65829.375,
"vertebrae_L3": 73551.375,
"vertebrae_L4": 78... |
s0321 | spine | [
[
1.5,
0,
0,
-200.6015625
],
[
0,
1.5,
0,
-55.6015625
],
[
0,
0,
1.5,
63.099998474121094
],
[
0,
0,
0,
1
]
] | [
272,
272,
303
] | {
"vertebrae_L1": {
"name": "vertebrae_L1",
"label_id": 31,
"centroid_mm": [
6.909057547381764,
138.0179130330447,
376.1019999445892
],
"volume_mm3": 41313.375
},
"vertebrae_L2": {
"name": "vertebrae_L2",
"label_id": 30,
"centroid_mm": [
8.389619633230666,
... | {
"A": [
[
0.002574002574002574,
0,
0,
0.49318291505791506
],
[
0,
0.003236245954692557,
0,
-0.11132180420711973
],
[
0,
0,
0.002244668911335578,
-0.15173961498119212
],
[
0,
0,
0,
1
]
]
} | {
"pid": "s0321",
"ok": true,
"reason": null,
"targets_present": [
"vertebrae_L1",
"vertebrae_L2",
"vertebrae_L3",
"vertebrae_L4",
"vertebrae_L5"
],
"target_volumes_mm3": {
"vertebrae_L1": 41316.75,
"vertebrae_L2": 43824.375,
"vertebrae_L3": 47820.375,
"vertebrae_L4": 494... |
End of preview.
Lumbar spine patient assets for cross-patient ultrasound navigation
417 patients derived from TotalSegmentator v2.0.1, prepared so that a synthetic ultrasound frame can be rendered at any surface-constrained probe pose.
No ultrasound images are stored here. Frames are rendered on the fly from the CT, the labels and the skin height map, so these assets are independent of which renderer you use — model-based, pix2pix, or your own.
Layout
patients/<pid>/
ct.npy (ni,nj,nk) int16 CT resampled to 1.5 mm isotropic, Hounsfield units
labels.npy (ni,nj,nk) uint8 merged TotalSegmentator ids, 0 = background
affine.npy (4,4) float64 voxel (i,j,k) -> patient world mm
heightmap.npz skin height + outward normal over the (x,z) grid
surface.npz skin point cloud with normals
manifest.json organ set, L1-L5 centroids and volumes, QC record
splits/full.json the frozen experiment split
splits/debug.json 12 ids for pipeline debugging, a subset of the above
prepare_report.json provenance for all 1228 source cases
ct.npy and labels.npy are deliberately uncompressed .npy: the loader opens
them with mmap_mode="r", so a whole population stays openable without fitting in RAM.
Splits — by patient, never by frame
| split | patients |
|---|---|
| train | 292 |
| validation | 42 |
| test | 83 |
| debug (subset of the above) | 12 |
Two frames from one subject share an anatomy, so a frame-level split leaks the test anatomy. Any atlas or population prior must be built from train only.
How the cohort was selected
TotalSegmentator v2.0.1 1228 cases
-> resample to 1.5 mm isotropic, merge masks keeping the original ids,
body mask from CT, skin height map + normals, QC
672 accepted
-> require all of L1-L5 present and reachable from the back
417 shipped here
Rejections:
| reason | cases |
|---|---|
| all targets below minimum volume | 384 |
| body truncated by FOV | 112 |
| no target has a reachable surface | 60 |
Loading
import json, numpy as np
pid = "s0004"
ct = np.load(f"patients/{pid}/ct.npy", mmap_mode="r") # do not load eagerly
labels = np.load(f"patients/{pid}/labels.npy", mmap_mode="r")
affine = np.load(f"patients/{pid}/affine.npy")
manifest = json.load(open(f"patients/{pid}/manifest.json"))
l4 = manifest["targets"]["vertebrae_L4"]
l4["label_id"], l4["centroid_mm"] # the target, in patient world mm
Total size: 35.7 GB.
Attribution
Derived from the TotalSegmentator dataset (Wasserthal et al., Radiology: Artificial Intelligence, 2023), released under CC BY 4.0; this derivative keeps that licence. The surface parameterisation and 3-DoF action space follow SonoGym (NeurIPS 2025 Datasets & Benchmarks).
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