twente-microbubblesim: restructure the data card to the common layout

Syncs the twente-microbubblesim card on the Hub with the reviewed state on GitHub (open-h/OpenH-RF).

The card now follows the layout shared by every OpenH-RF dataset: frontmatter with a `name`, a stand-alone title, the hero image with an italic caption linking the sample it shows, Description, Contributor(s), Creation Date and the standard CC BY 4.0 text, then a new **Processing the Dataset** section (the `zea process` command where the pipeline carries the whole reconstruction, and the `reconstruct.py` link) followed by Dataset Format, which opens with the zea version. Hard line breaks are gone so the Hub wraps paragraphs itself; the longer sections keep their content.

The usage example now matches the script (`PATH` / `PULSE` / `CONFIG_PATH` constants instead of CLI flags).

**GitHub PRs:**
- [tristan-deep/OpenH-RF#28](https://github.com/tristan-deep/OpenH-RF/pull/28) — Restructure all data cards to the common README layout

Files changed: 1.

```
~ twente-microbubblesim/README.md
```

twente-microbubblesim/README.md

@@ -1,5 +1,6 @@
 ---
-pretty_name: "OpenH-RF — Waveform-Specific Synthetic Microbubble RF Dataset"
+name: twente-microbubblesim
+pretty_name: "Waveform-Specific Synthetic Microbubble RF Dataset"
 license: cc-by-4.0
 task_categories:
   - image-to-image
@@ -15,26 +16,18 @@ size_categories:
   - "n<1K"
 ---
 
-# OpenH-RF synthetic ultrasound data
+# Waveform-Specific Synthetic Microbubble RF Dataset
 
 ## Dataset Description
 
-This synthetic 3-D ultrasound dataset contains nonlinear radiofrequency (RF)
-responses from microbubble contrast agents for cardiovascular-flow imaging. It
-was generated to study the effect of ultrasound transmit-waveform shape on RF
-signals and deep-learning methods for microbubble super-resolution. It contains
-simulated data, not clinical, phantom, or in-vivo animal data.
+This synthetic 3-D ultrasound dataset contains nonlinear radiofrequency (RF) responses from microbubble contrast agents for cardiovascular-flow imaging. It was generated to study the effect of ultrasound transmit-waveform shape on RF signals and deep-learning methods for microbubble super-resolution. It contains simulated data, not clinical, phantom, or in-vivo animal data.
 
-## Dataset Contributors
+## Dataset Contributor(s)
 
-| Contributor | Affiliation / role | Email |
-|---|---|---|
-| Rienk Zorgdrager | PhD candidate, University of Twente | `r.c.zorgdrager@utwente.nl` |
-| Anass Hameddine | PhD candidate, University of Twente | `a.hameddine@utwente.nl` |
-| Michel Versluis | Professor, physical and medical acoustics, University of Twente | `m.versluis@utwente.nl` |
-| Guillaume Lajoinie | Associate Professor, Physics of Fluids Group, University of Twente | `g.p.r.lajoinie@utwente.nl` |
-
-**Primary contacts:** Anass Hameddine and Rienk Zorgdrager.
+- Rienk Zorgdrager <r.c.zorgdrager@utwente.nl> (PhD candidate, University of Twente; primary contact)
+- Anass Hameddine <a.hameddine@utwente.nl> (PhD candidate, University of Twente; primary contact)
+- Michel Versluis <m.versluis@utwente.nl> (Professor, physical and medical acoustics, University of Twente)
+- Guillaume Lajoinie <g.p.r.lajoinie@utwente.nl> (Associate Professor, Physics of Fluids Group, University of Twente)
 
 ## Dataset Creation Date
 
@@ -42,82 +35,50 @@ simulated data, not clinical, phantom, or in-vivo animal data.
 
 ## License / Terms of Use
 
-This dataset is released under the Creative Commons Attribution 4.0
-International license (CC BY 4.0). See [creativecommons.org/licenses/by/4.0](https://creativecommons.org/licenses/by/4.0/). The contributors
-confirm that the simulated RF outputs, bubble ground truth, pulse waveforms,
-calibrated P4-1 inputs, and incorporated assets used to produce this dataset
-are cleared for public redistribution under CC BY 4.0, consistent with the
-accepted proposal and the steering-group IP policy.
+[Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/legalcode.en). Retain attribution and identify modifications when reusing the data.
 
 ## Intended Usage
 
-The dataset is intended for studying the effect of transmit waveforms on
-deep-learning methods for microbubble super-resolution imaging.
+The dataset is intended for studying the effect of transmit waveforms on deep-learning methods for microbubble super-resolution imaging.
 
 ## Dataset Characterization
 
 - **Data collection method:** Synthetic.
-- **Ground truth:** Simulated 3-D microbubble positions are stored as zea custom
-  elements (`bubble_x`, `bubble_y`, and `bubble_z`).
-- **Bubble populations:** Monodisperse bubbles with a radius of 2.4 micrometres
-  and 5% standard deviation, and a polydisperse SonoVue population.
-- **Acquisition system:** An experimentally calibrated virtual ATL P4-1
-  transducer with 96 elements, realistic 3-D plane-wave pressure fields, a
-  62.5 MHz RF sampling rate, and 12 transmit waveforms. The overall probe
-  dimensions are 0.02854 m × 0.016 m; each element is 0.000245 m wide and
-  0.016 m high. Its official nominal operating band is 1.0e6–4.0e6 Hz.
-- **Simulation scale:** Up to 27.5 microbubbles/cm³, with 250 random bubble
-  distributions per population.
-- **Bubble-response model:** The implementation is a modified private derivative
-  of the simulator described in Zorgdrager et al. (2025). It uses a custom,
-  parallelized radial microbubble-response solver based on the Rayleigh–Plesset
-  equation and adds 3-D realistic pressure-field calculation and coupling for
-  the calibrated virtual ATL P4-1. The exact source-code version was not
-  separately recorded; the dataset was generated with the internal label
-  **private dataset-generation release 2026-07-12**. The solver source is
-  private and is not distributed with this dataset.
+- **Ground truth:** Simulated 3-D microbubble positions are stored as zea custom elements (`bubble_x`, `bubble_y`, and `bubble_z`).
+- **Bubble populations:** Monodisperse bubbles with a radius of 2.4 micrometres and 5% standard deviation, and a polydisperse SonoVue population.
+- **Acquisition system:** An experimentally calibrated virtual ATL P4-1 transducer with 96 elements, realistic 3-D plane-wave pressure fields, a 62.5 MHz RF sampling rate, and 12 transmit waveforms. The overall probe dimensions are 0.02854 m × 0.016 m; each element is 0.000245 m wide and 0.016 m high. Its official nominal operating band is 1.0e6–4.0e6 Hz.
+- **Simulation scale:** Up to 27.5 microbubbles/cm³, with 250 random bubble distributions per population.
+- **Bubble-response model:** The implementation is a modified private derivative of the simulator described in Zorgdrager et al. (2025). It uses a custom, parallelized radial microbubble-response solver based on the Rayleigh–Plesset equation and adds 3-D realistic pressure-field calculation and coupling for the calibrated virtual ATL P4-1. The exact source-code version was not separately recorded; the dataset was generated with the internal label **private dataset-generation release 2026-07-12**. The solver source is private and is not distributed with this dataset.
+
+## Processing the Dataset
+
+The acquisitions can be processed with the `reconstruct.py` [script](https://github.com/open-h/OpenH-RF/blob/main/datasets/twente-microbubblesim/reconstruct.py) as provided in the [OpenH-RF GitHub repository](https://github.com/open-h/OpenH-RF), together with the pipeline definitions in `pipeline/` and the [zea library](https://github.com/tue-bmd/zea). The script streams the data from the Hugging Face Hub.
+
+Every pulse track has its own verified pipeline file, `pipeline/pipeline_track_<index>_<label>.yaml`, all defining the same chain:
+
+`demodulate → downsample (factor 1) → delay-and-sum beamform → envelope detect → normalize → log compress`
+
+Set `PATH` to one `.hdf5` acquisition, `PULSE` to the pulse label (for example `REF`, `DPT` or `L1.7`) and `CONFIG_PATH` to the matching track's pipeline. The script applies that track's beamforming peak-time reference (`custom/track_i_t_peak`) and, with `SHOW_BUBBLES`, overlays the ground-truth bubble positions.
 
 ## Dataset Format
 
-Each bubble distribution is stored in one zea HDF5 file containing 12 pulse
-tracks. The raw channel data in every `tracks/track_i/data/raw_data` dataset
-have shape `(1, 1, 8446, 96, 1)`: one frame, one transmit, 8,446 time samples,
-96 receive elements, and one real RF channel. RF values are `float32`; their
-absolute amplitude unit remains source-defined.
+[zea v0.1.6](https://github.com/tue-bmd/zea)
+
+Each bubble distribution is stored in one zea HDF5 file containing 12 pulse tracks. The raw channel data in every `tracks/track_i/data/raw_data` dataset have shape `(1, 1, 8446, 96, 1)`: one frame, one transmit, 8,446 time samples, 96 receive elements, and one real RF channel. RF values are `float32`; their absolute amplitude unit remains source-defined.
 
 The complete track hierarchy is:
 
-    tracks/
-    ├── track_0/
-    │   ├── label              # scalar string: DPT
-    │   ├── data/raw_data
-    │   ├── scan/
-    │   └── transmit_only
-    ├── track_1/               # label: L1.7
-    ├── ...
-    └── track_11/              # label: SUC
-
-Each track stores one pulse variant. The fixed mapping for `track_0` through
-`track_11` is `DPT`, `L1.7`, `L2.5`, `L3.4`, `LDC`, `LUC`, `REF`, `S1.7`,
-`S2.5`, `S3.4`, `SDC`, and `SUC`. Every track has its own canonical scalar
-`label` dataset. The same ordered names are also stored in
-`custom/pulse_names`. The tracks are independent pulse variants for the same bubble realization, not a temporal sequence; no `track_schedule` is used.
-
-Track-specific pulse metadata use names such as
-`custom/track_0_pulse_waveform` and `custom/track_0_t_peak`. The `scan` group
-contains sampling, transmit, timing, focus, steering, and apodization
-parameters. `transmit_only` is false because each track contains receive RF
-data. The probe geometry is stored at `probe/probe_geometry` with shape
-`(96, 3)`, one `(x, y, z)` position per receive element in metres. Element dimensions are stored at `probe/element_width` (`0.000245` m) and `probe/element_height` (`0.016` m). Overall probe dimensions are stored in metres as custom fields `probe_overall_width` (`0.02854`) and `probe_overall_height` (`0.016`). The official nominal P4-1 bandwidth is stored in `custom/probe_nominal_bandwidth_lower_frequency` and `custom/probe_nominal_bandwidth_upper_frequency` as 1.0e6–4.0e6 Hz.
-
-The conversion preserves the source RF traces and the available bubble,
-domain, and pulse metadata. It does not refocus or demodulate RF data before
-packaging. The source pulse waveforms were sampled at 250 MHz.
+    tracks/ ├── track_0/ │   ├── label              # scalar string: DPT │   ├── data/raw_data │   ├── scan/ │   └── transmit_only ├── track_1/               # label: L1.7 ├── ... └── track_11/              # label: SUC
+
+Each track stores one pulse variant. The fixed mapping for `track_0` through `track_11` is `DPT`, `L1.7`, `L2.5`, `L3.4`, `LDC`, `LUC`, `REF`, `S1.7`, `S2.5`, `S3.4`, `SDC`, and `SUC`. Every track has its own canonical scalar `label` dataset. The same ordered names are also stored in `custom/pulse_names`. The tracks are independent pulse variants for the same bubble realization, not a temporal sequence; no `track_schedule` is used.
+
+Track-specific pulse metadata use names such as `custom/track_0_pulse_waveform` and `custom/track_0_t_peak`. The `scan` group contains sampling, transmit, timing, focus, steering, and apodization parameters. `transmit_only` is false because each track contains receive RF data. The probe geometry is stored at `probe/probe_geometry` with shape `(96, 3)`, one `(x, y, z)` position per receive element in metres. Element dimensions are stored at `probe/element_width` (`0.000245` m) and `probe/element_height` (`0.016` m). Overall probe dimensions are stored in metres as custom fields `probe_overall_width` (`0.02854`) and `probe_overall_height` (`0.016`). The official nominal P4-1 bandwidth is stored in `custom/probe_nominal_bandwidth_lower_frequency` and `custom/probe_nominal_bandwidth_upper_frequency` as 1.0e6–4.0e6 Hz.
+
+The conversion preserves the source RF traces and the available bubble, domain, and pulse metadata. It does not refocus or demodulate RF data before packaging. The source pulse waveforms were sampled at 250 MHz.
 
 ### Pulse labels
 
-The meanings and waveform values below are from Table I of Zorgdrager et al.
-(2025), [doi:10.1109/TUFFC.2025.3537298](https://doi.org/10.1109/TUFFC.2025.3537298).
+The meanings and waveform values below are from Table I of Zorgdrager et al. (2025), [doi:10.1109/TUFFC.2025.3537298](https://doi.org/10.1109/TUFFC.2025.3537298).
 
 | Track | Label meaning | Frequency / sweep |
 |---:|---|---:|
@@ -138,8 +99,7 @@ The meanings and waveform values below are from Table I of Zorgdrager et al.
 
 **Current OpenH-RF release:** 500 HDF5 files; 17.03 GB (17,029,267,456 bytes) stored; root `zea_version` **0.1.6**. Sizes include all HDF5 contents and use decimal units (MB = 10^6 bytes, GB = 10^9 bytes, TB = 10^12 bytes), not decoded-array memory or original-source download sizes.
 
-- **Acquisition files:** 500 files, each with 12 one-frame pulse tracks (6,000
-  track acquisitions total).
+- **Acquisition files:** 500 files, each with 12 one-frame pulse tracks (6,000 track acquisitions total).
 - **Organization:** Two bubble populations × 250 files × 12 pulse tracks.
 - **Total consolidated HDF5 size:** 17.03 GB (17,029,267,456 bytes).
 
@@ -161,61 +121,17 @@ The zea 0.1.6 migration uses the following lowercase custom-field names:
 | `custom/bubble_p_dB` | `custom/bubble_p_db` |
 | `custom/track_<i>_pulse_A` | `custom/track_<i>_pulse_a` for tracks 0 through 11 |
 
-In the [upstream simulator](https://github.com/POF-ultrasound/super-resolution-waveforms/blob/main/RF_simulator/microbubble-simulator/main.m),
-`R0` is the initial microbubble radius in metres, whereas `r0` is the distance
-from the bubble to the pressure sensor in metres. The distinct
-`custom/bubble_r0` field is therefore retained unchanged, not merged with
-`custom/bubble_initial_r0`. These definitions describe the public upstream
-implementation; the dataset uses a private derivative. Existing stored units
-and values are preserved, not inferred or rescaled during migration.
+In the [upstream simulator](https://github.com/POF-ultrasound/super-resolution-waveforms/blob/main/RF_simulator/microbubble-simulator/main.m), `R0` is the initial microbubble radius in metres, whereas `r0` is the distance from the bubble to the pressure sensor in metres. The distinct `custom/bubble_r0` field is therefore retained unchanged, not merged with `custom/bubble_initial_r0`. These definitions describe the public upstream implementation; the dataset uses a private derivative. Existing stored units and values are preserved, not inferred or rescaled during migration.
 
-All 14 renames preserve array values, shapes, dtypes, and existing attributes.
-Each renamed dataset records its original name in `source_custom_name`.
-The current release uses the migrated names; older revisions use the original names. The loading helper
-accepts both; new consumers should use the migrated paths.
+All 14 renames preserve array values, shapes, dtypes, and existing attributes. Each renamed dataset records its original name in `source_custom_name`. The current release uses the migrated names; older revisions use the original names. The loading helper accepts both; new consumers should use the migrated paths.
 
 ## Subject Metadata
 
-This fully synthetic dataset contains no human or animal subjects, protected
-health information, age, sex, pathology, consent records, or clinical scanner
-identifiers.
-
-## Reconstruction
-
-All pulse tracks use identical verified pipeline files stored in the `pipeline/`
-folder: `pipeline_track_<index>_<label>.yaml` for each of the 12 tracks. Each
-file defines the verified processing chain:
-
-`demodulate → downsample (factor 1) → delay-and-sum beamform → envelope detect → normalize → log compress`
-
-`--pulse` selects the pulse by its stored label and applies the corresponding
-track's `t_peak`, while the same pipeline operations are applied to every
-track. These commands reconstruct REF (`track_6`) for both populations:
-
-```bash
-python reconstruct.py \
-  --path Monodispers/RFDATA00001.hdf5 \
-  --pulse REF \
-  --output REF_monodisperse.png
-
-python reconstruct.py \
-  --path SonoVue/RFDATA00001.hdf5 \
-  --pulse REF \
-  --output REF_sonovue.png
-```
-
-To override the selected track's pipeline, pass `--config-path`, for example
-`pipeline/pipeline_track_6_REF.yaml`. Each track stores its beamforming
-peak-time reference as `custom/track_i_t_peak`. Reconstruction
-applies the value belonging to the selected track. `--path` must point directly
-to one `.hdf5` acquisition file.
+This fully synthetic dataset contains no human or animal subjects, protected health information, age, sex, pathology, consent records, or clinical scanner identifiers.
 
 ## Data Validation
 
-All 500 HDF5 files were checked for the expected zea container structure, 12
-ordered and labelled tracks, RF shape `(1, 1, 8446, 96, 1)`, and track-specific
-pulse metadata. The original submission passed zea 0.1.2 validation. Representative RF traces and pulse
-waveforms were also compared with their pulse-folder sources with no mismatch.
+All 500 HDF5 files were checked for the expected zea container structure, 12 ordered and labelled tracks, RF shape `(1, 1, 8446, 96, 1)`, and track-specific pulse metadata. The original submission passed zea 0.1.2 validation. Representative RF traces and pulse waveforms were also compared with their pulse-folder sources with no mismatch.
 
 <table>
   <tr>
@@ -230,36 +146,19 @@ waveforms were also compared with their pulse-folder sources with no mismatch.
 
 ## Known Issues
 
-- The transmit setup is an unfocused plane wave by design: steering angle is
-  zero, no finite focus distance is used (`infinite focus`), transmit delays
-  are zero, and apodization is unity for every transmit element. These are
-  intentional simulation settings rather than missing calibration fields.
-- RF amplitude and several custom-element units remain source-defined and
-  should be confirmed against the simulator documentation.
-- The HDF5 files store only the official nominal bandwidth endpoints
-  (1.0–4.0 MHz). The measured transfer-function −6 dB bounds (approximately
-  1.52–3.70 MHz) and corresponding 83.4% fractional bandwidth are documented
-  in this README but are not stored as HDF5 data fields.
-- The simulator is a private, unpublished derivative of the cited simulator;
-  no public software package or Git commit is required to use the released RF
-  data. The internal dataset-generation release label is recorded in the HDF5
-  metadata and should be used when referring to this generation run.
+- The transmit setup is an unfocused plane wave by design: steering angle is zero, no finite focus distance is used (`infinite focus`), transmit delays are zero, and apodization is unity for every transmit element. These are intentional simulation settings rather than missing calibration fields.
+- RF amplitude and several custom-element units remain source-defined and should be confirmed against the simulator documentation.
+- The HDF5 files store only the official nominal bandwidth endpoints (1.0–4.0 MHz). The measured transfer-function −6 dB bounds (approximately 1.52–3.70 MHz) and corresponding 83.4% fractional bandwidth are documented in this README but are not stored as HDF5 data fields.
+- The simulator is a private, unpublished derivative of the cited simulator; no public software package or Git commit is required to use the released RF data. The internal dataset-generation release label is recorded in the HDF5 metadata and should be used when referring to this generation run.
 - No train/validation/test split is provided.
 - `reconstruct.py` imports `utils.py`; keep both files together.
 
 ## Ethical Considerations
 
-The dataset is synthetic, so participant consent, de-identification, and IRB
-approval are not applicable. The contributors confirm that the simulation code,
-calibrated inputs, source data, and incorporated assets may be redistributed
-under the declared CC BY 4.0 license, consistent with the accepted proposal and
-the steering-group IP policy.
+The dataset is synthetic, so participant consent, de-identification, and IRB approval are not applicable. The contributors confirm that the simulation code, calibrated inputs, source data, and incorporated assets may be redistributed under the declared CC BY 4.0 license, consistent with the accepted proposal and the steering-group IP policy.
 
 ## Citation
 
 When using the dataset, cite:
 
-R. Zorgdrager et al., “Waveform-Specific Performance of Deep Learning-Based
-Super-Resolution for Ultrasound Contrast Imaging,” *IEEE Transactions on
-Ultrasonics, Ferroelectrics, and Frequency Control*, 2025.
-[doi:10.1109/TUFFC.2025.3537298](https://doi.org/10.1109/TUFFC.2025.3537298)
+R. Zorgdrager et al., “Waveform-Specific Performance of Deep Learning-Based Super-Resolution for Ultrasound Contrast Imaging,” *IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control*, 2025. [doi:10.1109/TUFFC.2025.3537298](https://doi.org/10.1109/TUFFC.2025.3537298)