5 citations · 5 across the 7 of their papers we have counts for
8 papers
Graph Residual Noise Learner Network for Brain Connectivity Graph Prediction
Oytun Demirbilek, Tingying Peng, Alaa Bessadok
A morphological brain graph depicting a connectional fingerprint is of paramount importance for charting brain dysconnectivity patterns. Such data often has missing observations du…
Deep Cross-Modality and Resolution Graph Integration for Universal Brain Connectivity Mapping and Augmentation
Ece Cinar, Sinem Elif Haseki, Alaa Bessadok +1
The connectional brain template (CBT) captures the shared traits across all individuals of a given population of brain connectomes, thereby acting as a fingerprint. Estimating a CB…
A Few-shot Learning Graph Multi-Trajectory Evolution Network for Forecasting Multimodal Baby Connectivity Development from a Baseline Timepoint
Alaa Bessadok, Ahmed Nebli, Mohamed Ali Mahjoub +4
Charting the baby connectome evolution trajectory during the first year after birth plays a vital role in understanding dynamic connectivity development of baby brains. Such analys…
Inter-Domain Alignment for Predicting High-Resolution Brain Networks Using Teacher-Student Learning
Basar Demir, Alaa Bessadok, Islem Rekik
Accurate and automated super-resolution image synthesis is highly desired since it has the great potential to circumvent the need for acquiring high-cost medical scans and a time-c…
Graph Neural Networks in Network Neuroscience
Alaa Bessadok, Mohamed Ali Mahjoub, Islem Rekik
Noninvasive medical neuroimaging has yielded many discoveries about the brain connectivity. Several substantial techniques mapping morphological, structural and functional brain co…
Brain Multigraph Prediction using Topology-Aware Adversarial Graph Neural Network
Alaa Bessadok, Mohamed Ali Mahjoub, Islem Rekik
Brain graphs (i.e, connectomes) constructed from medical scans such as magnetic resonance imaging (MRI) have become increasingly important tools to characterize the abnormal change…
Residual Embedding Similarity-Based Network Selection for Predicting Brain Network Evolution Trajectory from a Single Observation
Ahmet Serkan Goktas, Alaa Bessadok, Islem Rekik
While existing predictive frameworks are able to handle Euclidean structured data (i.e, brain images), they might fail to generalize to geometric non-Euclidean data such as brain n…
Topology-Aware Generative Adversarial Network for Joint Prediction of Multiple Brain Graphs from a Single Brain Graph
Alaa Bessadok, Mohamed Ali Mahjoub, Islem Rekik
Several works based on Generative Adversarial Networks (GAN) have been recently proposed to predict a set of medical images from a single modality (e.g, FLAIR MRI from T1 MRI). How…