task_categories:image-classification size_categories:n<1K language:en license:openrail medical brain-data mri arxiv:2209.07162 region:us
This dataset was obtained as part of the Generative Modelling project from the Artificial Medical Intelligence Group - 
AMIGO (https://amigos.ai/). It consists on of 1,000 synthetic T1w images sampled from generative models trained on 
data originally from the UK Biobank dataset (https://www.ukbiobank.ac.uk/).
@misc{pinaya2022brain,
      title={Brain Imaging Generation with Latent Diffusion Models}, 
      author={Walter H. L. Pinaya and Petru-Daniel Tudosiu and Jessica Dafflon and Pedro F da Costa and Virginia Fernandez and Parashkev Nachev and Sebastien Ourselin and M. Jorge Cardoso},
      year={2022},
      eprint={2209.07162},
      archivePrefix={arXiv},
      primaryClass={eess.IV}
}
---
license: openrail
task_categories:
- image-classification
language:
- en
tags:
- medical
- brain-data
- mri
pretty_name: Brain imaging generation with Latent Diffusion Models
size_categories:
- n<1K
---
# Dataset Card for Brain imaging generation with Latent Diffusion Models

## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** [Amigo homepage](https://amigos.ai/)
- **Paper:** [Brain imaging generation with Latent Diffusion Models](https://arxiv.org/abs/2209.07162)
- **Point of Contact:** [Walter H. L. Pinaya](mailto:walter.diaz_sanz@kcl.ac.uk)

### Dataset Summary

This dataset was obtained as part of the Generative Modelling project from the Artificial Medical Intelligence Group - 
AMIGO (https://amigos.ai/). It consists on of 1,000 synthetic T1w images sampled from generative models trained on 
data originally from the UK Biobank dataset (https://www.ukbiobank.ac.uk/).

### Languages

The language in the dataset is English.

## Dataset Structure

### Data Instances

[More Information Needed]

### Data Fields

- `prompt_age`: a float value used during the sampling to specify the age of the generated brain image (defined in years) 
- `prompt_sex`: a string used during the sampling to specify the sex ("M" for male and "F" for female)
- `prompt_ventricular_volume`: a float whose value used during the sampling to specify the volume of ventricular cerebrospinal fluid (in mm^3; based on UKB Data-Field 25004)
- `prompt_brain_volume`: a float whose value used during the sampling to specify the brain volume normalised for head size (in mm^3; based on UKB Data-Field 25009)

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Licensing Information

The "Brain imaging generation with Latent Diffusion Models" dataset is released under the [OpenRAIL License](https://huggingface.co/blog/open_rail).

### Citation Information

```
@inproceedings{pinaya2022brain,
  title={Brain imaging generation with latent diffusion models},
  author={Pinaya, Walter HL and Tudosiu, Petru-Daniel and Dafflon, Jessica and Da Costa, Pedro F and Fernandez, Virginia and Nachev, Parashkev and Ourselin, Sebastien and Cardoso, M Jorge},
  booktitle={MICCAI Workshop on Deep Generative Models},
  pages={117--126},
  year={2022},
  organization={Springer}
}
```

### Contributions

Thanks to [@Warvito](https://github.com/Warvito) for adding this dataset.