The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: UnicodeDecodeError
Message: 'utf-8' codec can't decode byte 0x93 in position 0: invalid start byte
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3496, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2257, in _head
return next(iter(self.iter(batch_size=n)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2461, in iter
for key, example in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1974, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 503, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 350, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/text/text.py", line 73, in _generate_tables
batch = f.read(self.config.chunksize)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 813, in read_with_retries
out = read(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "<frozen codecs>", line 322, in decode
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x93 in position 0: invalid start byteNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
AneuG-Flow Dataset
Dataset Description
AneuG-Flow is a comprehensive dataset for intracranial aneurysm hemodynamics, containing computational fluid dynamics (CFD) simulations of blood flow through synthetic aneurysm morphologies generated by a generative model AneuG [1].
Dataset Summary
This dataset provides:
- 730 aneurysm cases with transient (time-varying) flow simulations
- High-resolution 3D geometries (original and remeshed)
- Blood flow data and wall shear stress
- Flow split ratios and inlet boundary conditions
- Pre-processed and assembled data for machine learning applications
Dataset Structure
Data Instances
The dataset is organized into three main directories:
1. steady_data/
Contains steady-state simulation data:
raw_data.pth: Raw steady-state simulation results
2. transient_data/ (~3GB for each case)
Contains 730 individual case folders (stable_*) with:
shape.obj: Original aneurysm geometry meshshape_remeshed.obj: Remeshed geometry for simulationblood_data.pt: Transient blood flow simulation results (PyTorch tensor)wall_data.pt: Transient Wall Shear Stress (PyTorch tensor)inlet_centroids.csv: 3D coordinates of inlet boundary points (x, y, z)flowsplit_ratio.txt: Flow split ratios at outletscheckpoint.npy: AneuG checkpoints
3. processed_data/ (~32GB)
Pre-processed and assembled data ready for machine learning:
assembled_registered_data_1k_v4.pth: Assembled transient flow dataassembled_registered_steady_data_1k_v4.pth: Assembled steady-state flow data
4. Geometries.zip
Compressed archive of geometry files.
Licensing Information
This dataset is released under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license.
Citation Information
If you wish to use this dataset in your research, please cite the following publication:
[1] Ding, W., Ji, K., Castro, S., Luo, Y., Roi, D., Yap, C.H.: Two-Stage Generative Model for Intracranial Aneurysm Meshes with Morphological Marker Conditioning. Medical Image Computing and Computer Assisted Intervention – MICCAI 2025, Lecture Notes in Computer Science 15969, 595--604 (2025).
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