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@@ -96,6 +96,61 @@ Simulation-based testing is constrained to the parameter variability represented
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  There is a risk of misjudging model performance if the simulated examples do not capture the variability in real patients. Please
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  see the paper for a full discussion of biases, risks, and limitations.
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  ## Citation
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  ```
 
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  There is a risk of misjudging model performance if the simulated examples do not capture the variability in real patients. Please
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  see the paper for a full discussion of biases, risks, and limitations.
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+ ## How to use it
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+ The msynth dataset is a very large dataset so for most use cases it is recommended to make use of the streaming API of `datasets`.
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+ The msynth dataset has three configurations: 1) device_data, 2) segmentation_mask, and 3) metadata
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+ You can load and iterate through the dataset using the configurations with the following lines of code:
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+
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+ ```python
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+ from datasets import load_dataset
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+ ds = load_dataset("didsr/msynth", 'device_data') # For device data for all breast density, mass redius, mass density, and relative dose, change configuration to 'segmentation_mask' and 'metadata' to load the segmentation masks and bound information
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+ print(ds_data["device_data"])
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+
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+ # A sample data instance
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+
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+ {'Raw': '~\\.cache\\huggingface\\datasets\\downloads\\extracted\\59384cf05fc44e8c0cb23bb19e1fcd8f0c39720b282109d204a85561fe66bdb1\\SIM\\P2_5.0_fatty.8336179.1\\1\\projection_DM1.raw',
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+ 'mhd': '~/.cache/huggingface/datasets/downloads/extracted/59384cf05fc44e8c0cb23bb19e1fcd8f0c39720b282109d204a85561fe66bdb1/SIM/P2_5.0_fatty.8336179.1/1\\projection_DM1.mhd',
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+ 'loc': '~/.cache/huggingface/datasets/downloads/extracted/59384cf05fc44e8c0cb23bb19e1fcd8f0c39720b282109d204a85561fe66bdb1/SIM/P2_5.0_fatty.8336179.1/1\\projection_DM1.loc',
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+ 'dcm': '~/.cache/huggingface/datasets/downloads/extracted/59384cf05fc44e8c0cb23bb19e1fcd8f0c39720b282109d204a85561fe66bdb1/SIM/P2_5.0_fatty.8336179.1/1\\DICOM_dm\\000.dcm',
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+ 'density': 'fatty',
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+ 'mass_radius': 5.0}
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+ ```
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+ Msynth dataset can also be loaded using custom breast density, mass redius, mass density, and relative dose information
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ # Dataset properties. change to 'all' to include all the values of breast density, mass redius, mass density, and relative dose information
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+ config_kwargs = {
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+ "lesion_density": ["1.0"],
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+ "dose": ["20%"],
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+ "density": ["fatty"],
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+ "size": ["5.0"]
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+ }
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+
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+ # Loading device data
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+ ds_data = load_dataset("didsr/msynth", 'device_data', **config_kwargs)
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+ # Loading segmentation-mask
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+ ds_seg = load_dataset("didsr/msynth", 'segmentation_mask', **config_kwargs)
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+ ```
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+ The meta data can also be loaded using the datasets API. An example of using metadata is given in **Demo:** [https://github.com/DIDSR/msynth-release/tree/master/examples](https://github.com/DIDSR/msynth-release/tree/master/examples)
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+
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+ ```python
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+ from datasets import load_dataset
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+ # Loading metadata
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+ ds_meta = load_dataset("didsr/msynth", 'metadata')
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+
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+ # A sample data instance
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+ ds_meta['metadata'][0]
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+
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+ # Output
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+
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+ {'fatty': '~\\.cache\\huggingface\\datasets\\downloads\\extracted\\3ea85fc6b3fcc253ac8550b5d1b21db406ca9a59ea125ff8fc63d9b754c88348\\bounds\\bounds_fatty.npy',
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+ 'dense': '~\\.cache\\huggingface\\datasets\\downloads\\extracted\\3ea85fc6b3fcc253ac8550b5d1b21db406ca9a59ea125ff8fc63d9b754c88348\\bounds\\bounds_dense.npy',
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+ 'hetero': '~\\.cache\\huggingface\\datasets\\downloads\\extracted\\3ea85fc6b3fcc253ac8550b5d1b21db406ca9a59ea125ff8fc63d9b754c88348\\bounds\\bounds_hetero.npy',
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+ 'scattered': '~\\.cache\\huggingface\\datasets\\downloads\\extracted\\3ea85fc6b3fcc253ac8550b5d1b21db406ca9a59ea125ff8fc63d9b754c88348\\bounds\\bounds_scattered.npy'}
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+
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+ ```
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  ## Citation
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  ```