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MGN-Net: a multi-view graph normalizer for integrating heterogeneous biological network populations


Apr 04, 2021
Islem Rekik, Mustafa Burak Gurbuz


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Deep Graph Normalizer: A Geometric Deep Learning Approach for Estimating Connectional Brain Templates


Dec 28, 2020
Mustafa Burak Gurbuz, Islem Rekik

* International Conference on Medical Image Computing and Computer-Assisted Intervention 2020 
* 11 pages, 2 figures 

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Deep EvoGraphNet Architecture For Time-Dependent Brain Graph Data Synthesis From a Single Timepoint


Sep 28, 2020
Ahmed Nebli, Ugur Ali Kaplan, Islem Rekik


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Multi-View Brain HyperConnectome AutoEncoder For Brain State Classification


Sep 24, 2020
Alin Banka, Inis Buzi, Islem Rekik


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Multi-Scale Profiling of Brain Multigraphs by Eigen-based Cross-Diffusion and Heat Tracing for Brain State Profiling


Sep 24, 2020
Mustafa Saglam, Islem Rekik


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Adversarial Brain Multiplex Prediction From a Single Network for High-Order Connectional Gender-Specific Brain Mapping


Sep 24, 2020
Ahmed Nebli, Islem Rekik


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Foreseeing Brain Graph Evolution Over Time Using Deep Adversarial Network Normalizer


Sep 23, 2020
Zeynep Gurler, Ahmed Nebli, Islem Rekik


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Residual Embedding Similarity-Based Network Selection for Predicting Brain Network Evolution Trajectory from a Single Observation


Sep 23, 2020
Ahmet Serkan Goktas, Alaa Bessadok, Islem Rekik


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GSR-Net: Graph Super-Resolution Network for Predicting High-Resolution from Low-Resolution Functional Brain Connectomes


Sep 23, 2020
Megi Isallari, Islem Rekik


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Topology-Aware Generative Adversarial Network for Joint Prediction of Multiple Brain Graphs from a Single Brain Graph


Sep 23, 2020
Alaa Bessadok, Mohamed Ali Mahjoub, Islem Rekik


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Supervised Multi-topology Network Cross-diffusion for Population-driven Brain Network Atlas Estimation


Sep 23, 2020
Islem Mhiri, Mohamed Ali Mahjoub, Islem Rekik


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Deep Hypergraph U-Net for Brain Graph Embedding and Classification


Aug 30, 2020
Mert Lostar, Islem Rekik


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Neuropsychiatric Disease Classification Using Functional Connectomics -- Results of the Connectomics in NeuroImaging Transfer Learning Challenge


Jun 05, 2020
Markus D. Schirmer, Archana Venkataraman, Islem Rekik, Minjeong Kim, Stewart Mostofsky, Mary Beth Nebel, Keri Rosch, Karen Seymour, Deana Crocetti, Hassna Irzan, Michael Hütel, Sebastien Ourselin, Neil Marlow, Andrew Melbourne, Egor Levchenko, Shuo Zhou, Mwiza Kunda, Haiping Lu, Nicha C. Dvornek, Juntang Zhuang, Gideon Pinto, Sandip Samal, Jorge L. Bernal-Rusiel, Rudolph Pienaar, Ai Wern Chung

* CNI-TLC was held in conjunction with MICCAI 2019 

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Machine Learning Methods for Brain Network Classification: Application to Autism Diagnosis using Cortical Morphological Networks


Apr 28, 2020
Ismail Bilgen, Goktug Guvercin, Islem Rekik


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Image Evolution Trajectory Prediction and Classification from Baseline using Learning-based Patch Atlas Selection for Early Diagnosis


Jul 13, 2019
Can Gafuroglu, Islem Rekik


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Dynamic Multiscale Tree Learning Using Ensemble Strong Classifiers for Multi-label Segmentation of Medical Images with Lesions


Sep 05, 2017
Samya Amiri, Mohamed Ali Mahjoub, Islem Rekik


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