There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Jiongqi Qu |
| Institution: | University College London |
| Department: | Medical Physics and Biomedical Engineering |
| Country: | |
| Proposed Analysis: | The proposed analysis is a four-year study that contains 1-year MRes and 3-year PhD. It focuses on optimising neuroimaging biomarkers for dementia using deep learning. Neuroimaging plays a key role in our understanding and treatment of dementia, and many biomarkers reflecting the brain’s health have been proposed. However, these neuroimaging biomarkers are currently limited by poor generalisability, inadequate robustness to varying types and quality of data, slow computation speeds and arbitrary processing methods. Emerging deep learning techniques have the potential to overcome these limitations; this project will involve the development of novel neural network architectures (e.g., transformers) and methods (e.g., synthetic image augmentation) to optimise MRI biomarkers of brain volume, ventricle size, cortical thickness, and white matter lesions for use in dementia research and clinical trials. |
| Additional Investigators |
