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Datasets:
AVS-Net
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knee_fast_mri

Size Categories: 100M<n<1B
Tags: medical
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The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code:   ConfigNamesError
Exception:    FileNotFoundError
Message:      Couldn't find a dataset script at /src/services/worker/AVS-Net/knee_fast_mri/knee_fast_mri.py or any data file in the same directory. Couldn't find 'AVS-Net/knee_fast_mri' on the Hugging Face Hub either: FileNotFoundError: No (supported) data files or dataset script found in AVS-Net/knee_fast_mri. 
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 55, in compute_config_names_response
                  for config in sorted(get_dataset_config_names(path=dataset, token=hf_token))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 351, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1491, in dataset_module_factory
                  raise FileNotFoundError(
              FileNotFoundError: Couldn't find a dataset script at /src/services/worker/AVS-Net/knee_fast_mri/knee_fast_mri.py or any data file in the same directory. Couldn't find 'AVS-Net/knee_fast_mri' on the Hugging Face Hub either: FileNotFoundError: No (supported) data files or dataset script found in AVS-Net/knee_fast_mri.

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Dataset for AVS-Net Pre-training

The dataset utilized in the pre-training of the AVS-Net: Attention-based Variable Splitting Network for P-MRI Acceleration model, developed by Y Zhang, J Li, Z Wang, J Duan, and J Li, incorporates data from five distinct protocol sequences. These are:

  • (coronal_pd)Coronal Spin Density-weighted without Fat Suppression
  • (coronal_pd_fs)Coronal Spin Density-weighted with Fat Suppression
  • (sagittal_pd)Sagittal Spin Density-weighted
  • (sagittal_t2)Sagittal T2-weighted with Fat Suppression
  • (axial_t2)Axial T2-weighted with Fat Suppression

The dataset is structured on a slice-by-slice basis, with each slice containing 20 cases. Each case is comprised of two files: rawdata*.mat and espirit*.mat. The dataset's structure can be outlined as follows:

Dataset architecture:

  • name: /rds/projects/d/duanj-ai-in-medical-imaging/knee_fast_mri
  • Protocol: [coronal_pd, coronal_pd_fs, sagittal_pd, sagittal_t2, axial_t2]

Approximately 40 slices per protocol, each slice containing 15 channels, with a height and width (HW) of (640, 368)

```
knee_nyu
    - axial_t2  coronal_pd(X)  coronal_pd_fs  sagittal_pd  sagittal_t2
        |           |           |               |           |
    - [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [11, 12, 13, 14, 15, 16, 17, 18, 19, 20] masks
                    |                                       |
    -            [train]                                  [val]
        |                                                            |
    - espirit*.mat(1-40), rawdata*.mat(1-40)                       *_masks.mat
```

In this structure, each protocol has approximately 40 slices, each consisting of 15 channels. The dimensions of the data are 640x368 (height x width). For each protocol, the slices are further divided into two groups: the training set ([train]) and the validation set ([val]). The training set includes the espirit*.mat and rawdata*.mat files for each slice, while the validation set contains *_masks.mat files.

Dataset Usage

For a standalone knee dataset download, use git lfs(https://git-lfs.com/) to download from the huggingface datasets(https://huggingface.co/datasets/AVS-Net/knee_fast_mri):

# Make sure you have git-lfs installed (https://git-lfs.com)
git lfs install
git clone -j8 git@hf.co:datasets/AVS-Net/knee_fast_mri

Known Issues and Resolutions

    1. Network Connection Issue

For enhanced network connection quality, it is recommended to employ the ssh protocol instead of https.

# Rather than utilizing `https://huggingface.co/datasets/AVS-Net/knee_fast_mri`
# Clone the repository using `git@hf.co:datasets/AVS-Net/knee_fast_mri`
# As an example:
git clone -j8 git@hf.co:datasets/AVS-Net/knee_fast_mri
    1. Interruptions During Download

Certain error messages may appear during the download process due to interruptions. These errors can include:

error: ... : cannot add to the index - missing --add option?
batch response: Post ... : read: connection reset by peer
error: failed to fetch some objects from 'https://hf.co/datasets/AVS-Net/knee_fast_mri.git/info/lfs'

Following the instructions below allows for the handling of these interruptions.

# Navigate (`cd`) to the directory containing the `lfs` folder
# Intead of using `git pull`,
# Use `git lfs pull` to resume the download progress for `lfs` projects

git lfs pull

Please note that this process will resume the download from where it was interrupted, thereby ensuring the integrity of your downloaded data.

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