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: | RUI ZOU |
| Institution: | Juntendo University Graduate School of Medicine |
| Department: | Data Science |
| Country: | |
| Proposed Analysis: | Perivascular spaces (PVS) are small fluid-filled structures surrounding blood vessels in the brain, and they are believed to play a role in the clearance of waste products from the brain. Abnormal PVS have been linked to a variety of neurological conditions, including Alzheimer's disease. The proposed analysis would involve developing a deep learning algorithm that can automatically grade PVS in clinical imaging data from ADNI participants with Alzheimer's disease. The algorithm would be based on a 3D convolutional neural network architecture and would be trained using labeled imaging data from ADNI. The proposed framework would be designed to be interpretable, meaning that the decisions made by the algorithm could be understood and explained by human experts. This would be achieved by incorporating techniques such as attention mechanisms and saliency maps into the algorithm. The ultimate goal of this proposed analysis would be to develop a tool that could assist clinicians in the diagnosis and monitoring of Alzheimer's disease by providing an automated and reliable way to grade PVS in clinical imaging data. |
| Additional Investigators |
