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: | Fakhri Ayadi |
| Institution: | Ecole supérieure privée d'ingénierie et de technologies |
| Department: | Informatics |
| Country: | |
| Proposed Analysis: | My research aims to apply deep learning techniques, specifically Convolutional Neural Networks (CNNs), for the classification of thousands of brain MRI images representing different stages: Alzheimer's Disease (AD), Normal Brain (CN), Mild Cognitive Impairment (MCI), Early Mild Cognitive Impairment (EMCI), and Late Mild Cognitive Impairment (LMCI). The dataset consists of images in NIFTI format, each associated with a patient. An accompanying CSV file contains columns for each image, each patient, and a classification label column (Alzheimer or Not Alzheimer) for each stage of disease (AD, CN, EMCI, LMCI, MCI). The objective is to develop a robust classification model capable of efficiently identifying the different stages of Alzheimer's disease from MRI images. This research aims to contribute to more accurate and early diagnoses, leveraging the power of deep learning and CNNs for medical image analysis. |
| Additional Investigators |
