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