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--- |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: test |
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path: data/test-* |
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dataset_info: |
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features: |
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- name: image |
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dtype: image |
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- name: line |
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dtype: string |
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- name: rad_score |
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dtype: string |
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- name: session |
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dtype: int64 |
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splits: |
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- name: train |
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num_bytes: 68961229.076 |
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num_examples: 1476 |
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- name: test |
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num_bytes: 68472028.992 |
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num_examples: 1674 |
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download_size: 137564710 |
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dataset_size: 137433258.06800002 |
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--- |
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# Dataset Card for mri-sym2 |
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### Dataset Summary |
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SymBrain, an annotated dataset of brain MRI images designed to advance the field of brain symmetry detection and segmentation. |
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Our dataset comprises a diverse collection of brain MRI T1w and T2w scans from the [dHCP](https://biomedia.github.io/dHCP-release-notes/download.html) dataset. |
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Each annotated to highlight the ideal **straight** mid-sagittal plane (MSP), demarcating the brain into two symmetrical hemispheres. |
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The accurate extraction of the MSP has the potential to greatly enhance segmentation precision. |
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Researchers and practitioners can utilize this dataset to devise innovative methods for enhanced brain MRI image segmentation. |
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SymBrain's rich and extensive content empowers the research community to address complex challenges in neuroimaging analysis, |
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ultimately contributing to advancements in medical diagnostics and treatment planning. |
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Symmetry analysis plays an important role in medical image processing, particularly in the detection of diseases and malformations. |
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SymBrain leverages the inherent bilateral symmetry observed in brain MRI images, |
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making it an invaluable resource for the development and evaluation |
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of automated algorithms aimed at detecting the symmetry axis within brain MRI data. |
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## Dataset Structure |
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The dataset contains 1476 T1w images types and 1674 T2w images. |
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The differences between the modalities lie in the intensity variations of the different brain areas. |
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All the images are accessible in the 'train' part of the dataset. |
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## Dataset Creation |
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### Loading the data |
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The dataset contains a 'train' split of 1476 rows, containing the t1 type images, and a 'test' split of 1674 rows, with the t2 type images. |
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```python |
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dataset = load_dataset("agucci/mri-sym2") |
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# first dataset example selection: |
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dataset['train'][0] |
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``` |
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**Attributes :** |
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- *image:* PIL image, shape (290, 290) |
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- *line:* Straight line annotation coordinates on the image. ({'x':x1, 'y':y1}, {'x':x2, 'y':y2}). Where (x1,y1), (x2,y2) are the starting and end points of the line. |
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- *radscore:* Radiology score of the volume the image was extracted from. Please refer to [dHCP doc](https://biomedia.github.io/dHCP-release-notes/download.html#metadata) for scores explanation. |
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- *session:* Session-ID of the original dataset, used for scan retrieval. |
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### Source Data |
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[dHCP](https://biomedia.github.io/dHCP-release-notes/download.html) dataset. |
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Three slices have been extracted from each of the 1050 3D volumes, creating 3150 images. |
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### Annotations |
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The authors did Annotations manually with the [V7lab tools](https://www.v7labs.com/). |
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### Licensing Information |
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[More Information Needed] |
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### Citation Information |
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When using the data please cite : |
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**authors papers coming soon** |
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and |
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**dhcp dataset** |
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Data were provided by the developing Human Connectome Project, KCL-Imperial- |
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Oxford Consortium funded by the European Research Council under the Eu- |
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ropean Union Seventh Framework Programme (FP/2007-2013) / ERC Grant |
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Agreement no. [319456]. We are grateful to the families who generously sup- |
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ported this trial. |
