Create README.md

README.md

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+---
+task_categories:
+- image-feature-extraction
+language:
+- en
+tags:
+- medical
+pretty_name: FlowOak
+size_categories:
+- 1K<n<10K
+---
+🧠 MRI Knee Dataset (Single-Coil)
+Dataset Name
+
+FLowOak/mri_knee
+
+📌 Dataset Summary
+
+FLowOak/mri_knee is a single-coil knee MRI dataset provided in HDF5 (.h5) format, intended for research in accelerated MRI reconstruction, compressed sensing, and deep learning–based image reconstruction.
+
+This dataset is derived from the fastMRI initiative and adapted for single-coil reconstruction experiments, making it suitable for lightweight models, NAS-based architectures, and academic research where computational resources are limited.
+
+📚 Credits & Acknowledgements
+
+⚠️ Important Credit Notice
+
+This dataset is based on data from the fastMRI dataset, a large-scale open dataset released by Facebook AI Research (FAIR) and NYU Langone Health.
+
+Original Dataset:
+
+fastMRI: An Open Dataset for Accelerated MRI
+
+Authors: Zbontar et al.
+
+Website: https://fastmri.org
+
+License: fastMRI Data License
+
+If you use FLowOak/mri_knee in your research, you must also cite fastMRI in addition to this dataset.
+
+📖 Recommended Citation
+Cite this dataset:
+@misc{flowoak_mri_knee,
+  title={MRI Knee Dataset (Single-Coil)},
+  author={FLowOak},
+  year={2025},
+  publisher={Hugging Face},
+  howpublished={\url{https://huggingface.co/datasets/FLowOak/mri_knee}}
+}
+
+Also cite fastMRI:
+@article{zbontar2018fastmri,
+  title={fastMRI: An Open Dataset and Benchmarks for Accelerated MRI},
+  author={Zbontar, Jure and Knoll, Florian and Sriram, Anuroop and others},
+  journal={arXiv preprint arXiv:1811.08839},
+  year={2018}
+}
+
+🧩 Dataset Structure
+
+File format: .h5 (HDF5)
+
+Imaging modality: MRI (Knee)
+
+Acquisition: Single-coil
+
+Domain: k-space and/or image domain (depending on file)
+
+Resolution: Typically centered and cropped (e.g., 320×320)
+
+ℹ️ The dataset does not currently expose predefined splits (train/validation/test) in the Hugging Face viewer. Users are expected to manage splits manually.
+
+📦 Expected HDF5 Contents
+
+Each .h5 file may contain one or more of the following keys:
+
+Key	Description
+kspace	Complex-valued undersampled k-space
+reconstruction_rss / image	Reference image (if available)
+mask	Sampling mask (optional)
+
+⚠️ Users should inspect each file using h5py to confirm exact structure.
+
+🚀 Intended Use
+
+This dataset is intended for research and educational purposes only, including:
+
+Single-coil MRI reconstruction
+
+Compressed sensing MRI
+
+Neural Architecture Search (NAS) for MRI
+
+Image-domain and k-space domain reconstruction
+
+Evaluation using PSNR, SSIM, NMSE
+
+🧪 Example Usage
+import h5py
+
+with h5py.File("sample.h5", "r") as f:
+    print(list(f.keys()))
+    kspace = f["kspace"][()]
+
+⚙️ Preprocessing Recommendations
+
+Convert complex data into real + imaginary channels
+
+Normalize magnitude values
+
+Apply FFT/IFFT for domain conversion
+
+Generate Cartesian or variable-density masks if not provided
+
+⚠️ Limitations
+
+Single-coil only (not multi-coil clinical reconstruction)
+
+No built-in Hugging Face dataset splits
+
+Requires custom data loading logic
+
+Derived from fastMRI, so original fastMRI license terms apply
+
+🧾 License
+
+This dataset follows the same usage restrictions as fastMRI.
+Please refer to the original fastMRI license:
+
+👉 https://fastmri.org/licensing/
+
+✅ Final Note
+
+This dataset is not a replacement for fastMRI, but a processed derivative designed to simplify single-coil MRI reconstruction research.