Alzheimer’s Disease (AD) and Parkinson’s Disease (PD) are the two most common neurodegenerative diseases caused by structural changes in the brain and lead to deterioration of cognitive functions. Patients usually experience diagnostic symptoms at later stages after irreversible neural damage occurs. Early detection of such diseases is crucial in maximising patients’ quality of life and to start treatments to decelerate the progress of the disease. Early detection may be possible via computer-assisted systems using neuro-imaging data. Among all, deep learning utilising magnetic resonance imaging (MRI) have become a prominent tool due to its capability to extract high-level features through local connectivity, weight sharing, and spatial invariance. This project investigates the detection of AD and PD by building various 2D and 3D convolutional models.
A 3D convolutional neural network (CNN) architecture for disease classification. 3D boxes show input and feature maps.

Project members

Team members

Acknowledgements

This project has received funding from the School of Computer Science and Electrical Engineering (CSEE) PhD Scholarship Programme.

Publications

  1. Yagis, E (2022). Diagnosis of Neurodegenerative Diseases using Deep Learning. PhD thesis.
  2. Yagis, E., Workalemahu Atnafu, S., Garcia Seco De Herrera, A., Marzi, C., Giannelli, M., Tessa, C., Citi, L. and Diciotti, S., (2021). Deep Learning in Neuroimaging: Effect of Data Leakage in Cross-validation Using 2D Convolutional Neural Networks. Scientific Reports. 11 (1), 22544-
  3. Yagis, Ekin and Garcia Seco De Herrera, Alba and Citi, Luca (2021) Convolutional Autoencoder based Deep Learning Approach for Alzheimer's Disease Diagnosis using Brain MRI. In: 2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS), 2021-06-07 - 2021-06-09.
  4. Yagis, E., Citi, L., Diciotti, S., Merzi, C., Workalemahu Atnafu, S. and Garcia Seco De Herrera, A., (2020). 3D Convolutional Neural Networks for Diagnosis of Alzheimer’s Disease via structural MRI. In: IEEE 33rd International Symposium on Computer Based Medical Systems (CBMS), (pp. 65-70)
  5. Yagis, E., Garcia Seco De Herrera, A. and Citi, L., (2019). Generalization Performance of the Deep Learning Models in Neurodegenerative Disease Classification. In: 10th International Workshop on Biomedical and Health Informatics (BHI), (pp. 1692-1698).