60 citations · 215 across the 55 of their papers we have counts for
13 papers · 1 filter
Deep Graph Normalizer: A Geometric Deep Learning Approach for Estimating Connectional Brain Templates
Mustafa Burak Gurbuz, Islem Rekik
A connectional brain template (CBT) is a normalized graph-based representation of a population of brain networks also regarded as an average connectome. CBTs are powerful tools for…
Deep EvoGraphNet Architecture For Time-Dependent Brain Graph Data Synthesis From a Single Timepoint
Ahmed Nebli, Ugur Ali Kaplan, Islem Rekik
Learning how to predict the brain connectome (i.e. graph) development and aging is of paramount importance for charting the future of within-disorder and cross-disorder landscape o…
Multi-View Brain HyperConnectome AutoEncoder For Brain State Classification
Alin Banka, Inis Buzi, Islem Rekik
Graph embedding is a powerful method to represent graph neurological data (e.g., brain connectomes) in a low dimensional space for brain connectivity mapping, prediction and classi…
Multi-Scale Profiling of Brain Multigraphs by Eigen-based Cross-Diffusion and Heat Tracing for Brain State Profiling
Mustafa Saglam, Islem Rekik
The individual brain can be viewed as a highly-complex multigraph (i.e. a set of graphs also called connectomes), where each graph represents a unique connectional view of pairwise…
Adversarial Brain Multiplex Prediction From a Single Network for High-Order Connectional Gender-Specific Brain Mapping
Ahmed Nebli, Islem Rekik
Brain connectivity networks, derived from magnetic resonance imaging (MRI), non-invasively quantify the relationship in function, structure, and morphology between two brain region…
Foreseeing Brain Graph Evolution Over Time Using Deep Adversarial Network Normalizer
Zeynep Gurler, Ahmed Nebli, Islem Rekik
Foreseeing the brain evolution as a complex highly inter-connected system, widely modeled as a graph, is crucial for mapping dynamic interactions between different anatomical regio…
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…
GSR-Net: Graph Super-Resolution Network for Predicting High-Resolution from Low-Resolution Functional Brain Connectomes
Megi Isallari, Islem Rekik
Catchy but rigorous deep learning architectures were tailored for image super-resolution (SR), however, these fail to generalize to non-Euclidean data such as brain connectomes. Sp…
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…
Supervised Multi-topology Network Cross-diffusion for Population-driven Brain Network Atlas Estimation
Islem Mhiri, Mohamed Ali Mahjoub, Islem Rekik
Estimating a representative and discriminative brain network atlas (BNA) is a nascent research field in mapping a population of brain networks in health and disease. Although limit…
Deep Hypergraph U-Net for Brain Graph Embedding and Classification
Mert Lostar, Islem Rekik
-Background. Network neuroscience examines the brain as a complex system represented by a network (or connectome), providing deeper insights into the brain morphology and function,…
Neuropsychiatric Disease Classification Using Functional Connectomics -- Results of the Connectomics in NeuroImaging Transfer Learning Challenge
Markus D. Schirmer, Archana Venkataraman, Islem Rekik +23
Large, open-source consortium datasets have spurred the development of new and increasingly powerful machine learning approaches in brain connectomics. However, one key question re…
Machine Learning Methods for Brain Network Classification: Application to Autism Diagnosis using Cortical Morphological Networks
Ismail Bilgen, Goktug Guvercin, Islem Rekik
Autism spectrum disorder (ASD) affects the brain connectivity at different levels. Nonetheless, non-invasively distinguishing such effects using magnetic resonance imaging (MRI) re…