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PICMUS - Plane-Wave Imaging Challenge in Medical UltraSound
This dataset is a zea-format (HDF5) conversion of the PICMUS (IEEE IUS 2016) challenge data for evaluating plane-wave image reconstruction quality.
| Property | Value |
|---|---|
| Modality | 2-D plane-wave ultrasound (IQ and RF) |
| Probe | Verasonics Vantage + L11-4v (128 elements, 5.208 MHz) |
| Partitions | Simulation, Experimental, In-vivo (carotid artery) |
| Data types | IQ (complex) and RF (real) channel data |
| Splits | simulation/, database/ (experimental), in_vivo/ |
Conversion
This dataset was downloaded, converted to zea format, and uploaded using the zea data converter:
python -m zea.data.convert picmus <src> <dst> --download
Dataset structure
simulation/
contrast_speckle/
contrast_speckle_simu_dataset_iq/
contrast_speckle_simu_dataset_iq.hdf5
...
database/
experiments/
contrast_speckle/
contrast_speckle_expe_dataset_iq/...
contrast_speckle_expe_dataset_rf/...
...
in_vivo/
carotid_long/
carotid_long_expe_dataset_iq/...
carotid_cross/
...
Each HDF5 file follows the zea data format and contains:
data/raw_data- channel data, shape(1, n_tx, n_ax, n_el, n_ch)wheren_ch=1for RF data andn_ch=2(I/Q) for IQ datascan/- plane-wave acquisition parameters (angles, delays, geometry, …)metadata/- subject type and citation credit
License
The datasets and code provided on PICMUS are free of use. The only request is to refer properly to PICMUS - The Plane Wave Imaging Challenge in Medical UltraSound and quote the proceeding paper.
Citation
If you use this dataset, please cite:
@inproceedings{liebgott2016picmus,
title = {Plane-Wave Imaging Challenge in Medical Ultrasound},
author = {Liebgott, Herve and Rodriguez-Molares, Alfonso and
Cervenansky, Frederic and D'hooge, Jan and Bernard, Olivier},
booktitle = {2016 IEEE International Ultrasonics Symposium (IUS)},
pages = {1--4},
year = {2016},
doi = {10.1109/ULTSYM.2016.7728908}
}
Links
- PICMUS challenge: https://www.creatis.insa-lyon.fr/Challenge/IEEE_IUS_2016/
- Download page: https://www.creatis.insa-lyon.fr/Challenge/IEEE_IUS_2016/download
- zea toolkit: https://github.com/tue-bmd/zea
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