Research Projects
Alzheimer’s Disease
Alzheimer’s disease (AD) is a neurological disorder with symptoms such as deterioration of cognitive function, memory loss, and problems with language and behavior issues. It involves an increasing in amyloid beta and tau protein in the brain, leading to the formation of plaques and tangles that impair normal cerebral function. According to the 2024 World Alzheimer Report, 55 million people worldwide were living with AD in 2019, this number is projected to rise to 139 million in 2050. As the underlying causes of AD are not fully understood, there is currently no treatment. However, research suggests AD begins developing a decade or more before clinical symptoms become apparent. Consequently, accurate and early detection is crucial, as it can slow disease progression, improve patients’ quality of life, extend lifespan, and play a vital role in drug development and public health. Despite its importance, its early detection remains challenging due to the subtle onset of symptoms and limited awareness and resources, particularly in low- and middle-income countries.
This project aims to develop efficient signal processing and machine learning methods to help with diagnosis and prognosis of AD.
Participating Members
Selected publications
Journals
Pham Minh Tuan, Le Quoc Anh, Trung Thanh Le, Trong-Le Phan, Mouloud Adel, Salah Bourennane, Ismail Burak Parlak, Eric Guedj, Guy Nagels, and Nguyen Linh Trung. Novel PET-driven brain mapping for Alzheimer’s diagnosis: Integrated feature extraction and ranking capabilities. APSIPA Transactions on Signal and Information Processing, June 2026. [accepted].
Pham Minh Tuan, Tatiana Horowitz, Mouloud Adel, Julien Wojak, Nguyen Linh Trung, and Eric guedj. Comparative evaluation of graph construction methods for individual brain metabolic network from FDG-PET images: an ADNI study in healthy subjects. European Journal of Nuclear Medicine and Molecular Imaging (EJNMMI), 53:1139–1154, January 2026.
Duy-Thanh Vu, Duy-Cat Can, Christelle Schneuwly Diaz, Julien S. Bodelet, Guillaume E. Blanc, Huy Phan, Gilles Allali, Viet-Dung Nguyen, Hengyi Cao, Xingru He, Yannick Muller, Bangdong Zhi, Haochang Shou, Haoyu Zhang, Wei He, Xiaojun Wang, Marcus Munafo, Guy Nagels, Philippe Ryvlin, Nguyen Linh Trung, Giuseppe Pantaleo, and Oliver Y. Chen. Residual partial least squares learning: Brain cortical thickness simultaneously predicts eight non-pairwise-correlated behavioural and disease outcomes in Alzheimer’s disease. NeuroImage, October 2025. [under review].
Pham Minh Tuan, Mouloud Adel, Nguyen Linh Trung, Tatiana Horowitz, Ismail Burak Parlak, and Eric guedj. FDG-PET-based brain network analysis: A brief review of metabolic connectivity. European Journal of Nuclear Medicine and Molecular Imaging Reports (EJNMMI Reports), 9(4):1–28, January 2025.
Pham Minh Tuan, Mouloud Adel, Nguyen Linh Trung, and Eric Guedj. Enhancing feature selection in MCI diagnosis using FDG-PET images: Leveraging multiple simple autoencoder architectures. REV Journal on Electronics and Communications, 14(2):19–27, April–June 2024.
Pham Minh Tuan, Mouloud Adel, Eric Guedj, and Nguyen Linh Trung. Multi-scale metabolic brain connectivity construction: application to Alzheimer’s disease computer-aided diagnosis. Transactions on Computer Science and Applications, May 2024.
Pham Minh Tuan, Trong-Le Phan, Mouloud Adel, Eric Guedj, and Nguyen Linh Trung. Autoencoder-based feature ranking for Alzheimer disease classification using PET image. Machine Learning with Applications, 6:100184, December 2021.
Conferences
Le Quoc Anh, Nguyen Tien Dung, Nguyen Phuong Trang, Pham Minh Tuan, Thanh Trung Le, Nguyen Thanh Trung, Sara de Witte, Mouloud Adel, Ismail Burak Parlak, Karim Abed-Meraim, Jeroen Van Schependom, Sebastiaan Engelborghs, Guy Nagels, and Nguyen Linh Trung. Metabolic networks on PET-based C-Atlas for diagnosis of Alzheimer’s disease. 9th International Conference on Multimedia Analysis and Pattern Recognition (MAPR), Hue, Vietnam, 13–14 August 2026. [accepted].
Pham Minh Tuan, Julien Wojak, Mouloud Adel, Eric Guedj, and Nguyen Linh Trung. Feature aggregation for alzheimer’s disease diagnosis using fdg-pet images: The potential of graph-based methods. 2026 IEEE International Symposium on Biomedical Imaging (ISBI), London, United Kingdom, 8–11 April 2026.
Tuan Minh Pham, Julien Wojak, Mouloud Adel, Burak Parlak, Nguyen Linh Trung, and Eric Guedj. Does brain network construction choice matter? an empirical study of individual networks from static FDG-PET for Alzheimer’s diagnosis. 14th International Conference on Image Processing Theory, Tools and Applications (IPTA), Istanbul, Turkey, 13–16 October 2025.
Pham Minh Tuan, Mouloud Adel, Nguyen Linh Trung, and Eric Guedj. Does brain atlas choice matter? An empirical study in Alzheimer’s diagnosis using FDG-PET images. 2024 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA-ASC), Macau, China, 3–6 December 2024.
Pham Minh Tuan, Mouloud Adel, Nguyen Linh Trung, and Eric Guedj. Evaluating graph-building methods for enhanced Alzheimer’s disease diagnosis using FDG-PET and graph neural networks. 2024 International Symposium on Nonlinear Theory and its Applications (NOLTA), Halong, Vietnam, 3–6 December 2024.
Vu Duy Thanh, Trung Thanh Le, Pham Minh Tuan, Nguyen Linh Trung, Karim Abed-Meraim, Mouloud Adel, Nguyen Viet Dung, Nguyen Thanh Trung, Dinh Doan Long, and Oliver C. Chen. Tensor kernel learning for classification of Alzheimer’s conditions based on multimodal data. 7th International Conference on Multimedia Analysis and Pattern Recognition (MAPR), Danang, Vietnam, 14–15 August 2024.
Pham Minh Tuan, Mouloud Adel, Nguyen Linh Trung, and Eric Guedj. Enhancing depression diagnosis using FDG-PET images with hypergraphs. 32nd European Signal Processing Conference (EUSIPCO), pages 1461–1465, Lyon, France, August 2024.
Pham Minh Tuan, Mouloud Adel, Nguyen Linh Trung, and Eric Guedj. Wasserstein-based distance for constructing multi-scale individual brain networks from FDG-PET images: Application to Alzheimer’s disease diagnosis. 32nd European Signal Processing Conference (EUSIPCO), pages 1441–1445, Lyon, France, August 2024.
Nguyen Duc Kien, Fahimeh Akbarian, Jorne Laton, Sebastiaan Engelborghs, Jeroen Van Schependom, Nguyen Linh Trung, and Guy Nagels. Value of periodic and aperiodic EEG components to detect cognitive deterioration. 32nd European Signal Processing Conference (EUSIPCO), pages 1446–1450, Lyon, France, August 2024.
Pham Minh Tuan, Mouloud Adel, Nguyen Linh Trung, and Eric Guedj. Dynamic time warping-based distance for constructing individual brain networks from FDG-PET images: Application to Alzheimer’s disease. 12th International Conference on Image Processing Theory, Tools and Applications (IPTA), Paris, France, October 2023.
Pham Minh Tuan, Nguyen Linh Trung, Mouloud Adel, and Eric Guedj. Autoencoder-based feature ranking for predicting mild cognitive impairment conversion using FDG-PET images. 22nd IEEE Statistical Signal Processing Workshop (SSP), Hanoi, Vietnam, July 2023.
Pham Minh Tuan, Le-Trong Phan, Mouloud Adel, Salah Bourennane, and Nguyen Linh Trung. C-atlas: A brain mapping based on FDG-PET images for Alzheimer’s disease diagnosis. 16th International Conference on Computing and Communication Technologies (RIVF), Ho Chi Minh city, Vietnam, December 2022.