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2020 – today
- 2025
[e22]Islem Rekik
, Ehsan Adeli, Sang Hyun Park, Celia Cintas:
Predictive Intelligence in Medicine - 7th International Workshop, PRIME 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings. Lecture Notes in Computer Science 15155, Springer 2025, ISBN 978-3-031-74560-7 [contents]- [e21]Islem Rekik, Ehsan Adeli, Sang Hyun Park, Celia Cintas:
Predictive Intelligence in Medicine - 7th International Workshop, PRIME 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings. Lecture Notes in Computer Science 15155, Springer 2025, ISBN 978-3-031-74560-7 [contents] - [e20]Esther Puyol-Antón, Ghada Zamzmi, Aasa Feragen, Andrew P. King, Veronika Cheplygina, Melanie Ganz-Benjaminsen, Enzo Ferrante, Ben Glocker, Eike Petersen, John S. H. Baxter, Islem Rekik, Roy Eagleson:
Ethics and Fairness in Medical Imaging - Second International Workshop on Fairness of AI in Medical Imaging, FAIMI 2024, and Third International Workshop on Ethical and Philosophical Issues in Medical Imaging, EPIMI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6-10, 2024, Proceedings. Lecture Notes in Computer Science 15198, Springer 2025, ISBN 978-3-031-72786-3 [contents] - [e19]Xuanang Xu, Zhiming Cui, Islem Rekik, Xi Ouyang, Kaicong Sun:
Machine Learning in Medical Imaging - 15th International Workshop, MLMI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings, Part I. Lecture Notes in Computer Science 15241, Springer 2025, ISBN 978-3-031-73283-6 [contents] - [e18]Xuanang Xu, Zhiming Cui, Islem Rekik, Xi Ouyang, Kaicong Sun:
Machine Learning in Medical Imaging - 15th International Workshop, MLMI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings, Part II. Lecture Notes in Computer Science 15242, Springer 2025, ISBN 978-3-031-73292-8 [contents] - 2024
- [j40]Tianming Liu, Dajiang Zhu, Fei Wang, Islem Rekik, Xia Ben Hu, Dinggang Shen:
Editorial Special Issue on Explainable and Generalizable Deep Learning for Medical Imaging. IEEE Trans. Neural Networks Learn. Syst. 35(6): 7271-7274 (2024) - [c89]Haotian Jiang, Shu Zhang, Xuyun Wen, Hui Cui, Jun Lu, Islem Rekik, Jiquan Ma, Geng Chen:
Self-Supervised Denoising of Diffusion MRI Data Via Spatio-Angular Noise2Noise. ISBI 2024: 1-5 - [c88]Scarlet Xiao, Islem Rekik:
DynGNN: Dynamic Memory-Enhanced Generative GNNs for Predicting Temporal Brain Connectivity. PRIME@MICCAI 2024: 111-123 - [c87]Pragya Singh, Islem Rekik:
Strongly Topology-Preserving GNNs for Brain Graph Super-Resolution. PRIME@MICCAI 2024: 124-136 - [c86]Mayssa Soussia, Mohamed Ali Mahjoub, Islem Rekik:
Generative Hypergraph Neural Network for Multiview Brain Connectivity Fusion. PRIME@MICCAI 2024: 137-148 - [c85]Jiameng Liu, Feihong Liu, Kaicong Sun, Yuhang Sun, Jiawei Huang, Caiwen Jiang, Islem Rekik, Dinggang Shen:
UinTSeg: Unified Infant Brain Tissue Segmentation with Anatomy Delineation. MICCAI (2) 2024: 487-497 - [c84]Atefe Hassani, Islem Rekik:
UniFed: A Universal Federation of a Mixture of Highly Heterogeneous Medical Image Classification Tasks. MLMI@MICCAI (2) 2024: 32-42 - [c83]Jiameng Liu, Furkan Pala, Islem Rekik, Dinggang Shen:
DHSampling: Diversity-Based Hyperedge Sampling in GNN Learning with Application to Medical Imaging Classification. MLMI@MICCAI (1) 2024: 402-411 - [e17]Xiaohuan Cao, Xuanang Xu, Islem Rekik, Zhiming Cui, Xi Ouyang:
Machine Learning in Medical Imaging - 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings, Part I. Lecture Notes in Computer Science 14348, Springer 2024, ISBN 978-3-031-45672-5 [contents] - [e16]Xiaohuan Cao, Xuanang Xu, Islem Rekik, Zhiming Cui, Xi Ouyang:
Machine Learning in Medical Imaging - 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings, Part II. Lecture Notes in Computer Science 14349, Springer 2024, ISBN 978-3-031-45675-6 [contents] - [i45]Michalis Pistos, Gang Li, Weili Lin, Dinggang Shen, Islem Rekik:
Predicting Infant Brain Connectivity with Federated Multi-Trajectory GNNs using Scarce Data. CoRR abs/2401.01383 (2024) - [i44]Geng Chen, Qingyue Wang, Islem Rekik:
Metadata-Driven Federated Learning of Connectional Brain Templates in Non-IID Multi-Domain Scenarios. CoRR abs/2403.09139 (2024) - [i43]Atefe Hassani, Islem Rekik:
UniFed: A Universal Federation of a Mixture of Highly Heterogeneous Medical Image Classification Tasks. CoRR abs/2408.07075 (2024) - 2023
- [j39]Zeynep Gürler, Mohammed Amine Gharsallaoui, Islem Rekik, Alzheimer's Disease Neuroimaging Initiative:
Template-based graph registration network for boosting the diagnosis of brain connectivity disorders. Comput. Medical Imaging Graph. 103: 102140 (2023) - [j38]Mert Can Kurucu, Islem Rekik, Alzheimer's Disease Neuroimaging Initiative:
Graph neural network based unsupervised influential sample selection for brain multigraph population fusion. Comput. Medical Imaging Graph. 108: 102274 (2023) - [j37]Oytun Demirbilek, Islem Rekik, Alzheimer's Disease Neuroimaging Initiative:
Predicting the evolution trajectory of population-driven connectional brain templates using recurrent multigraph neural networks. Medical Image Anal. 83: 102649 (2023) - [j36]Nada Chaari, Hatice Camgöz-Akdag, Islem Rekik:
Comparative survey of multigraph integration methods for holistic brain connectivity mapping. Medical Image Anal. 85: 102741 (2023) - [j35]Alaa Bessadok, Mohamed Ali Mahjoub, Islem Rekik:
Graph Neural Networks in Network Neuroscience. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 5833-5848 (2023) - [j34]Zeynep Gürler, Islem Rekik:
Federated Brain Graph Evolution Prediction Using Decentralized Connectivity Datasets With Temporally-Varying Acquisitions. IEEE Trans. Medical Imaging 42(7): 2022-2031 (2023) - [c82]Dimitrios Proios, Anthony Yazdani, Alban Bornet, Julien Ehrsam, Islem Rekik, Douglas Teodoro:
Leveraging patient similarities via graph neural networks to predict phenotypes from temporal data. DSAA 2023: 1-10 - [c81]Emircan Gündogdu, Islem Rekik:
Template-Based Federated Multiview Domain Alignment for Predicting Heterogeneous Brain Graph Evolution Trajectories from Baseline. PRIME@MICCAI 2023: 14-24 - [c80]Jia Ji, Islem Rekik:
Federated Multimodal and Multiresolution Graph Integration for Connectional Brain Template Learning. DGM4MICCAI 2023: 14-24 - [c79]Christopher Adnel, Islem Rekik:
Affordable Graph Neural Network Framework Using Topological Graph Contraction. MILLanD@MICCAI 2023: 35-46 - [c78]Hizir Can Bayram, Mehmet Serdar Çelebi, Islem Rekik:
RepNet for Quantifying the Reproducibility of Graph Neural Networks in Multiview Brain Connectivity Biomarker Discovery. PRIME@MICCAI 2023: 35-45 - [c77]Nishant Rajadhyaksha, Islem Rekik:
Diffusion-Based Graph Super-Resolution with Application to Connectomics. PRIME@MICCAI 2023: 96-107 - [c76]Michalis Pistos, Gang Li, Weili Lin, Dinggang Shen, Islem Rekik:
Federated Multi-trajectory GNNs Under Data Limitations for Baby Brain Connectivity Forecasting. PRIME@MICCAI 2023: 120-133 - [c75]Chun Xu, Islem Rekik:
Federated Multi-domain GNN Network for Brain Multigraph Generation. PRIME@MICCAI 2023: 194-205 - [c74]Doga Türkseven, Islem Rekik, Christoph von Tycowicz, Martin Hanik:
Predicting Shape Development: A Riemannian Method. ShapeMI@MICCAI 2023: 211-222 - [c73]Ramona Ghilea, Islem Rekik:
Replica-Based Federated Learning with Heterogeneous Architectures for Graph Super-Resolution. MLMI@MICCAI (2) 2023: 273-282 - [e15]Stefan Wesarg, Esther Puyol-Antón, John S. H. Baxter, Marius Erdt, Klaus Drechsler, Cristina Oyarzun Laura, Moti Freiman, Yufei Chen, Islem Rekik, Roy Eagleson, Aasa Feragen, Andrew P. King, Veronika Cheplygina, Melanie Ganz-Benjaminsen, Enzo Ferrante, Ben Glocker, Daniel Moyer, Eike Petersen:
Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging - 12th International Workshop, CLIP 2023 1st International Workshop, FAIMI 2023 and 2nd International Workshop, EPIMI 2023 Vancouver, BC, Canada, October 8 and October 12, 2023 Proceedings. Lecture Notes in Computer Science 14242, Springer 2023, ISBN 978-3-031-45248-2 [contents] - [e14]Islem Rekik, Ehsan Adeli, Sang Hyun Park, Celia Cintas, Ghada Zamzmi:
Predictive Intelligence in Medicine - 6th International Workshop, PRIME 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings. Lecture Notes in Computer Science 14277, Springer 2023, ISBN 978-3-031-46004-3 [contents] - [i42]Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah, Alejandro F. Frangi, Alena Buyx, Anais Emelie, Andrea Lara, Antonio R. Porras, An-Wen Chan, Arcadi Navarro, Ben Glocker, Benard Ohene Botwe, Bishesh Khanal, Brigit Beger, Carol C. Wu, Celia Cintas, Curtis P. Langlotz, Daniel Rueckert, Deogratias Mzurikwao, Dimitrios I. Fotiadis, Doszhan Zhussupov, Enzo Ferrante, Erik Meijering, Eva Weicken, Fabio A. González, Folkert W. Asselbergs, Fred W. Prior, Gabriel P. Krestin, Gary S. Collins, Geletaw Sahle Tegenaw, Georgios Kaissis, Gianluca Misuraca, Gianna Tsakou, Girish Dwivedi, Haridimos Kondylakis, Harsha Jayakody, Henry C. Woodruff, Hugo J. W. L. Aerts, Ian Walsh, Ioanna Chouvarda, Irène Buvat, Islem Rekik, James S. Duncan, Jayashree Kalpathy-Cramer, Jihad Zahir, Jinah Park, John Mongan, Judy W. Gichoya, Julia A. Schnabel, et al.:
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare. CoRR abs/2309.12325 (2023) - [i41]Bobby Azad, Reza Azad, Sania Eskandari, Afshin Bozorgpour, Amirhossein Kazerouni, Islem Rekik, Dorit Merhof:
Foundational Models in Medical Imaging: A Comprehensive Survey and Future Vision. CoRR abs/2310.18689 (2023) - [i40]Christopher Adnel, Islem Rekik:
FALCON: Feature-Label Constrained Graph Net Collapse for Memory Efficient GNNs. CoRR abs/2312.16542 (2023) - [i39]Ramona Ghilea, Islem Rekik:
Replica Tree-based Federated Learning using Limited Data. CoRR abs/2312.17159 (2023) - 2022
- [j33]Ahmed Nebli, Mohammed Amine Gharsallaoui, Zeynep Gürler, Islem Rekik, Alzheimer's Disease Neuroimaging Initiative:
Quantifying the reproducibility of graph neural networks using multigraph data representation. Neural Networks 148: 254-265 (2022) - [j32]Nada Chaari, Mohammed Amine Gharsallaoui, Hatice Camgöz-Akdag, Islem Rekik:
Multigraph classification using learnable integration network with application to gender fingerprinting. Neural Networks 151: 250-263 (2022) - [c72]Jawher Ben Abdallah, Linda Marrakchi-Kacem, Islem Rekik:
Training Hacks and a Frugal Man's Net with Application to Glioblastoma Segmentation. ATSIP 2022: 1-4 - [c71]Zeynep Gürler, Islem Rekik:
Federated Time-Dependent GNN Learning from Brain Connectivity Data with Missing Timepoints. PRIME@MICCAI 2022: 1-12 - [c70]Ece Cinar, Sinem Elif Haseki, Alaa Bessadok, Islem Rekik:
Deep Cross-Modality and Resolution Graph Integration for Universal Brain Connectivity Mapping and Augmentation. ISGIE/GRAIL@MICCAI 2022: 89-98 - [c69]Selim Yürekli, Mehmet Arif Demirtas, Islem Rekik:
Quantifying the Predictive Uncertainty of Regression GNN Models Under Target Domain Shifts. PRIME@MICCAI 2022: 149-159 - [c68]Mehmet Yigit Balik, Arwa Rekik, Islem Rekik:
Investigating the Predictive Reproducibility of Federated Graph Neural Networks Using Medical Datasets. PRIME@MICCAI 2022: 160-171 - [c67]Furkan Pala, Islem Rekik:
Predicting Brain Multigraph Population from a Single Graph Template for Boosting One-Shot Classification. PRIME@MICCAI 2022: 191-202 - [c66]Imen Jegham, Islem Rekik:
Meta-RegGNN: Predicting Verbal and Full-Scale Intelligence Scores Using Graph Neural Networks and Meta-learning. PRIME@MICCAI 2022: 203-211 - [c65]Xuesong Wang, Lina Yao, Islem Rekik, Yu Zhang:
Contrastive Functional Connectivity Graph Learning for Population-based fMRI Classification. MICCAI (1) 2022: 221-230 - [c64]Fatih Said Duran, Abdurrahman Beyaz, Islem Rekik:
Dual-HINet: Dual Hierarchical Integration Network of Multigraphs for Connectional Brain Template Learning. MICCAI (1) 2022: 305-314 - [e13]Islem Rekik, Ehsan Adeli, Sang Hyun Park, Celia Cintas:
Predictive Intelligence in Medicine - 5th International Workshop, PRIME 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings. Lecture Notes in Computer Science 13564, Springer 2022, ISBN 978-3-031-16918-2 [contents] - [e12]Shadi Albarqouni, Spyridon Bakas, Sophia Bano, M. Jorge Cardoso, Bishesh Khanal, Bennett A. Landman, Xiaoxiao Li, Chen Qin, Islem Rekik, Nicola Rieke, Holger Roth, Debdoot Sheet, Daguang Xu:
Distributed, Collaborative, and Federated Learning, and Affordable AI and Healthcare for Resource Diverse Global Health - Third MICCAI Workshop, DeCaF 2022, and Second MICCAI Workshop, FAIR 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18 and 22, 2022, Proceedings. Lecture Notes in Computer Science 13573, Springer 2022, ISBN 978-3-031-18522-9 [contents] - [e11]Chunfeng Lian, Xiaohuan Cao, Islem Rekik, Xuanang Xu, Zhiming Cui:
Machine Learning in Medical Imaging - 13th International Workshop, MLMI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings. Lecture Notes in Computer Science 13583, Springer 2022, ISBN 978-3-031-21013-6 [contents] - [e10]John S. H. Baxter, Islem Rekik, Roy Eagleson, Luping Zhou, Tanveer F. Syeda-Mahmood, Hongzhi Wang, Mustafa Hajij:
Ethical and Philosophical Issues in Medical Imaging, Multimodal Learning and Fusion Across Scales for Clinical Decision Support, and Topological Data Analysis for Biomedical Imaging - 1st International Workshop, EPIMI 2022, 12th International Workshop, ML-CDS 2022, 2nd International Workshop, TDA4BiomedicalImaging, Held in Conjunction with MICCAI 2022, Singapore, September 18-22, 2022, Proceedings. Lecture Notes in Computer Science 13755, Springer 2022, ISBN 978-3-031-23222-0 [contents] - [i38]Kelei He, Chen Gan, Zhuoyuan Li, Islem Rekik, Zihao Yin, Wen Ji, Yang Gao, Qian Wang, Junfeng Zhang, Dinggang Shen:
Transformers in Medical Image Analysis: A Review. CoRR abs/2202.12165 (2022) - [i37]Xuesong Wang, Lina Yao, Islem Rekik, Yu Zhang:
Contrastive Graph Learning for Population-based fMRI Classification. CoRR abs/2203.14044 (2022) - [i36]Nada Chaari, Hatice Camgöz-Akdag, Islem Rekik:
Comparative Survey of Multigraph Integration Methods for Holistic Brain Connectivity Mapping. CoRR abs/2204.05110 (2022) - [i35]Furkan Pala, Islem Rekik:
Predicting Brain Multigraph Population From a Single Graph Template for Boosting One-Shot Classification. CoRR abs/2209.06005 (2022) - [i34]Mehmet Yigit Balik, Arwa Rekik, Islem Rekik:
Investigating the Predictive Reproducibility of Federated Graph Neural Networks using Medical Datasets. CoRR abs/2209.06032 (2022) - [i33]Ece Cinar, Sinem Elif Haseki, Alaa Bessadok, Islem Rekik:
Deep Cross-Modality and Resolution Graph Integration for Universal Brain Connectivity Mapping and Augmentation. CoRR abs/2209.13529 (2022) - [i32]Imen Jegham, Islem Rekik:
Meta-RegGNN: Predicting Verbal and Full-Scale Intelligence Scores using Graph Neural Networks and Meta-Learning. CoRR abs/2209.13530 (2022) - [i31]Doga Türkseven, Islem Rekik, Christoph von Tycowicz, Martin Hanik:
Predicting Shape Development: a Riemannian Method. CoRR abs/2212.04740 (2022) - [i30]Oben Özgür, Arwa Rekik, Islem Rekik:
Population Template-Based Brain Graph Augmentation for Improving One-Shot Learning Classification. CoRR abs/2212.07790 (2022) - 2021
- [j31]Ahmed Nebli, Islem Rekik:
Adversarial brain multiplex prediction from a single brain network with application to gender fingerprinting. Medical Image Anal. 67: 101843 (2021) - [j30]Olfa Ghribi, Gang Li, Weili Lin, Dinggang Shen, Islem Rekik:
Multi-Regression based supervised sample selection for predicting baby connectome evolution trajectory from neonatal timepoint. Medical Image Anal. 68: 101853 (2021) - [j29]Alaa Bessadok, Mohamed Ali Mahjoub, Islem Rekik:
Brain graph synthesis by dual adversarial domain alignment and target graph prediction from a source graph. Medical Image Anal. 68: 101902 (2021) - [j28]Markus D. Schirmer, Archana Venkataraman, Islem Rekik, Minjeong Kim, Stewart H. Mostofsky, Mary Beth Nebel, Keri Rosch, Karen Seymour, Deana Crocetti, Hassna Irzan, Michael Hütel, Sébastien Ourselin, Neil Marlow, Andrew Melbourne, Egor Levchenko, Shuo Zhou, Mwiza Kunda, Haiping Lu, Nicha C. Dvornek, Juntang Zhuang, Gideon Pinto, Sandip Samal, Jennings Zhang, Jorge L. Bernal-Rusiel, Rudolph Pienaar, Ai Wern Chung:
Neuropsychiatric disease classification using functional connectomics - results of the connectomics in neuroimaging transfer learning challenge. Medical Image Anal. 70: 101972 (2021) - [j27]Mustafa Burak Gurbuz, Islem Rekik:
MGN-Net: A multi-view graph normalizer for integrating heterogeneous biological network populations. Medical Image Anal. 71: 102059 (2021) - [j26]Megi Isallari, Islem Rekik:
Brain graph super-resolution using adversarial graph neural network with application to functional brain connectivity. Medical Image Anal. 71: 102084 (2021) - [j25]Alaa Bessadok, Mohamed Ali Mahjoub, Islem Rekik:
Brain multigraph prediction using topology-aware adversarial graph neural network. Medical Image Anal. 72: 102090 (2021) - [j24]Gaoxiang Chen, Jintao Ru, Yilin Zhou, Islem Rekik, Zhifang Pan, Xiaoming Liu, Yezhi Lin, Beichen Lu, Jialin Shi:
MTANS: Multi-Scale Mean Teacher Combined Adversarial Network with Shape-Aware Embedding for Semi-Supervised Brain Lesion Segmentation. NeuroImage 244: 118568 (2021) - [c63]Nesrine Bnouni, Hadil Ben Amor, Islem Rekik, Mohamed Salah Rhim, Basel Solaiman, Najoua Essoukri Ben Amara:
Boosting CNN Learning by Ensemble Image Preprocessing Methods for Cervical Cancer Segmentation. SSD 2021: 264-269 - [c62]Islem Mhiri, Ahmed Nebli, Mohamed Ali Mahjoub, Islem Rekik:
Non-isomorphic Inter-modality Graph Alignment and Synthesis for Holistic Brain Mapping. IPMI 2021: 203-215 - [c61]Alaa Bessadok, Ahmed Nebli, Mohamed Ali Mahjoub, Gang Li, Weili Lin, Dinggang Shen, Islem Rekik:
A Few-Shot Learning Graph Multi-trajectory Evolution Network for Forecasting Multimodal Baby Connectivity Development from a Baseline Timepoint. PRIME@MICCAI 2021: 11-24 - [c60]Umut Guvercin, Mohammed Amine Gharsallaoui, Islem Rekik:
One Representative-Shot Learning Using a Population-Driven Template with Application to Brain Connectivity Classification and Evolution Prediction. PRIME@MICCAI 2021: 25-36 - [c59]Hizir Can Bayram, Islem Rekik:
A Federated Multigraph Integration Approach for Connectional Brain Template Learning. ML-CDS@MICCAI 2021: 36-47 - [c58]Furkan Pala, Islem Mhiri, Islem Rekik:
Template-Based Inter-modality Super-Resolution of Brain Connectivity. PRIME@MICCAI 2021: 70-82 - [c57]Mohammed Amine Gharsallaoui, Furkan Tornaci, Islem Rekik:
Investigating and Quantifying the Reproducibility of Graph Neural Networks in Predictive Medicine. PRIME@MICCAI 2021: 104-116 - [c56]Islem Mhiri, Mohamed Ali Mahjoub, Islem Rekik:
StairwayGraphNet for Inter- and Intra-modality Multi-resolution Brain Graph Alignment and Synthesis. MLMI@MICCAI 2021: 140-150 - [c55]Alpay Tekin, Ahmed Nebli, Islem Rekik:
Recurrent Brain Graph Mapper for Predicting Time-Dependent Brain Graph Evaluation Trajectory. DART/FAIR@MICCAI 2021: 180-190 - [c54]Basar Demir, Alaa Bessadok, Islem Rekik:
Inter-domain Alignment for Predicting High-Resolution Brain Networks Using Teacher-Student Learning. DART/FAIR@MICCAI 2021: 203-215 - [c53]Guris Özen, Ahmed Nebli, Islem Rekik:
FLAT-Net: Longitudinal Brain Graph Evolution Prediction from a Few Training Representative Templates. PRIME@MICCAI 2021: 266-278 - [c52]Oytun Demirbilek, Islem Rekik:
Recurrent Multigraph Integrator Network for Predicting the Evolution of Population-Driven Brain Connectivity Templates. MICCAI (7) 2021: 584-594 - [e9]Islem Rekik, Ehsan Adeli, Sang Hyun Park, Julia A. Schnabel:
Predictive Intelligence in Medicine - 4th International Workshop, PRIME 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings. Lecture Notes in Computer Science 12928, Springer 2021, ISBN 978-3-030-87601-2 [contents] - [e8]Chunfeng Lian, Xiaohuan Cao, Islem Rekik, Xuanang Xu, Pingkun Yan:
Machine Learning in Medical Imaging - 12th International Workshop, MLMI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings. Lecture Notes in Computer Science 12966, Springer 2021, ISBN 978-3-030-87588-6 [contents] - [e7]Shadi Albarqouni, Manuel Jorge Cardoso, Qi Dou, Konstantinos Kamnitsas, Bishesh Khanal, Islem Rekik, Nicola Rieke, Debdoot Sheet, Sotirios A. Tsaftaris, Daguang Xu, Ziyue Xu:
Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health - Third MICCAI Workshop, DART 2021, and First MICCAI Workshop, FAIR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, Proceedings. Lecture Notes in Computer Science 12968, Springer 2021, ISBN 978-3-030-87721-7 [contents] - [i29]Islem Rekik, Mustafa Burak Gurbuz:
MGN-Net: a multi-view graph normalizer for integrating heterogeneous biological network populations. CoRR abs/2104.03895 (2021) - [i28]Megi Isallari, Islem Rekik:
Brain Graph Super-Resolution Using Adversarial Graph Neural Network with Application to Functional Brain Connectivity. CoRR abs/2105.00425 (2021) - [i27]Alaa Bessadok, Mohamed Ali Mahjoub, Islem Rekik:
Brain Multigraph Prediction using Topology-Aware Adversarial Graph Neural Network. CoRR abs/2105.02565 (2021) - [i26]Alaa Bessadok, Mohamed Ali Mahjoub, Islem Rekik:
Graph Neural Networks in Network Neuroscience. CoRR abs/2106.03535 (2021) - [i25]Martin Hanik, Mehmet Arif Demirtas, Mohammed Amine Gharsallaoui, Islem Rekik:
Predicting cognitive scores with graph neural networks through sample selection learning. CoRR abs/2106.09408 (2021) - [i24]Islem Mhiri, Ahmed Nebli, Mohamed Ali Mahjoub, Islem Rekik:
Non-isomorphic Inter-modality Graph Alignment and Synthesis for Holistic Brain Mapping. CoRR abs/2107.06281 (2021) - [i23]Mohammed Amine Gharsallaoui, Islem Rekik:
Quantifying the Reproducibility of Graph Neural Networks using Multigraph Brain Data. CoRR abs/2109.02248 (2021) - [i22]Seymanur Akti, Dogay Kamar, Özgür Anil Özlü, Ihsan Soydemir, Muhammet Akcan, Abdullah Kul, Islem Rekik:
A Comparative Study of Machine Learning Methods for Predicting the Evolution of Brain Connectivity from a Baseline Timepoint. CoRR abs/2109.07739 (2021) - [i21]Basar Demir, Alaa Bessadok, Islem Rekik:
Inter-Domain Alignment for Predicting High-Resolution Brain Networks Using Teacher-Student Learning. CoRR abs/2110.03452 (2021) - [i20]Oytun Demirbilek, Islem Rekik:
Recurrent Multigraph Integrator Network for Predicting the Evolution of Population-Driven Brain Connectivity Templates. CoRR abs/2110.03453 (2021) - [i19]Alaa Bessadok, Ahmed Nebli, Mohamed Ali Mahjoub, Gang Li, Weili Lin, Dinggang Shen, Islem Rekik:
A Few-shot Learning Graph Multi-Trajectory Evolution Network for Forecasting Multimodal Baby Connectivity Development from a Baseline Timepoint. CoRR abs/2110.03535 (2021) - [i18]Islem Mhiri, Mohamed Ali Mahjoub, Islem Rekik:
StairwayGraphNet for Inter- and Intra-modality Multi-resolution Brain Graph Alignment and Synthesis. CoRR abs/2110.04279 (2021) - [i17]Alpay Tekin, Ahmed Nebli, Islem Rekik:
Recurrent Brain Graph Mapper for Predicting Time-Dependent Brain Graph Evaluation Trajectory. CoRR abs/2110.11237 (2021) - [i16]Umut Guvercin, Mohammed Amine Gharsallaoui, Islem Rekik:
One Representative-Shot Learning Using a Population-Driven Template with Application to Brain Connectivity Classification and Evolution Prediction. CoRR abs/2110.11238 (2021) - 2020
- [j23]Salma Dhifallah, Islem Rekik, Alzheimer's Disease Neuroimaging Initiative:
Estimation of connectional brain templates using selective multi-view network normalization. Medical Image Anal. 59 (2020) - [j22]Islem Mhiri, Islem Rekik:
Joint functional brain network atlas estimation and feature selection for neurological disorder diagnosis with application to autism. Medical Image Anal. 60 (2020) - [j21]Oualid M. Benkarim, Gemma Piella, Islem Rekik, Nadine Hahner, Elisenda Eixarch, Dinggang Shen, Gang Li, Miguel Ángel González Ballester, Gerard Sanroma:
A novel approach to multiple anatomical shape analysis: Application to fetal ventriculomegaly. Medical Image Anal. 64: 101750 (2020) - [j20]Islem Mhiri, Anouar Ben Khalifa, Mohamed Ali Mahjoub, Islem Rekik:
Brain graph super-resolution for boosting neurological disorder diagnosis using unsupervised multi-topology connectional brain template learning. Medical Image Anal. 65: 101768 (2020) - [j19]Gaoxiang Chen, Qun Li, Fuqian Shi, Islem Rekik, Zhifang Pan:
RFDCR: Automated brain lesion segmentation using cascaded random forests with dense conditional random fields. NeuroImage 211: 116620 (2020) - [j18]Nicolas Georges, Islem Mhiri, Islem Rekik, Alzheimer's Disease Neuroimaging Initiative:
Identifying the best data-driven feature selection method for boosting reproducibility in classification tasks. Pattern Recognit. 101: 107183 (2020) - [c51]Mohammad Moussa Madine, Islem Rekik, Naoufel Werghi:
Diagnosing Autism Using T1-W MRI With Multi-Kernel Learning and Hypergraph Neural Network. ICIP 2020: 438-442 - [c50]Nesrine Bnouni, Islem Rekik, Mohamed Salah Rhim, Najoua Essoukri Ben Amara:
Context-Aware Synergetic Multiplex Network for Multi-organ Segmentation of Cervical Cancer MRI. PRIME@MICCAI 2020: 1-11 - [c49]Ahmet Serkan Goktas, Alaa Bessadok, Islem Rekik:
Residual Embedding Similarity-Based Network Selection for Predicting Brain Network Evolution Trajectory from a Single Observation. PRIME@MICCAI 2020: 12-23 - [c48]Mayssa Soussia, Xuyun Wen, Zhen Zhou, Bing Jin, Tae-Eui Kam, Li-Ming Hsu, Zhengwang Wu, Gang Li, Li Wang, Islem Rekik, Weili Lin, Dinggang Shen, Han Zhang:
A Computational Framework for Dissociating Development-Related from Individually Variable Flexibility in Regional Modularity Assignment in Early Infancy. MICCAI (7) 2020: 13-21 - [c47]Ahmed Nebli, Islem Rekik:
Adversarial Brain Multiplex Prediction from a Single Network for High-Order Connectional Gender-Specific Brain Mapping. PRIME@MICCAI 2020: 24-34 - [c46]Alin Banka, Inis Buzi, Islem Rekik:
Multi-view Brain HyperConnectome AutoEncoder for Brain State Classification. PRIME@MICCAI 2020: 101-110 - [c45]Ugur Demir, Mohammed Amine Gharsallaoui, Islem Rekik:
Clustering-Based Deep Brain MultiGraph Integrator Network for Learning Connectional Brain Templates. UNSURE/GRAIL@MICCAI 2020: 109-120 - [c44]Zeynep Gürler, Ahmed Nebli, Islem Rekik:
Foreseeing Brain Graph Evolution over Time Using Deep Adversarial Network Normalizer. PRIME@MICCAI 2020: 111-122 - [c43]Megi Isallari, Islem Rekik:
GSR-Net: Graph Super-Resolution Network for Predicting High-Resolution from Low-Resolution Functional Brain Connectomes. MLMI@MICCAI 2020: 139-149 - [c42]Mustafa Saglam, Islem Rekik:
Multi-scale Profiling of Brain Multigraphs by Eigen-Based Cross-diffusion and Heat Tracing for Brain State Profiling. UNSURE/GRAIL@MICCAI 2020: 142-151 - [c41]Ahmed Nebli, Ugur Ali Kaplan, Islem Rekik:
Deep EvoGraphNet Architecture for Time-Dependent Brain Graph Data Synthesis from a Single Timepoint. PRIME@MICCAI 2020: 144-155 - [c40]Mustafa Burak Gurbuz, Islem Rekik:
Deep Graph Normalizer: A Geometric Deep Learning Approach for Estimating Connectional Brain Templates. MICCAI (7) 2020: 155-165 - [c39]Islem Mhiri, Mohamed Ali Mahjoub, Islem Rekik:
Supervised Multi-topology Network Cross-Diffusion for Population-Driven Brain Network Atlas Estimation. MICCAI (7) 2020: 166-176 - [c38]Alaa Bessadok, Mohamed Ali Mahjoub, Islem Rekik:
Topology-Aware Generative Adversarial Network for Joint Prediction of Multiple Brain Graphs from a Single Brain Graph. MICCAI (7) 2020: 551-561 - [e6]Islem Rekik, Ehsan Adeli, Sang Hyun Park, Maria del C. Valdés Hernández:
Predictive Intelligence in Medicine - Third International Workshop, PRIME 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings. Lecture Notes in Computer Science 12329, Springer 2020, ISBN 978-3-030-59353-7 [contents] - [e5]Martin Reuter, Christian Wachinger, Hervé Lombaert, Beatriz Paniagua, Orcun Goksel, Islem Rekik:
Shape in Medical Imaging - International Workshop, ShapeMI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings. Lecture Notes in Computer Science 12474, Springer 2020, ISBN 978-3-030-61055-5 [contents] - [i15]Ismail Bilgen, Goktug Guvercin, Islem Rekik:
Machine Learning Methods for Brain Network Classification: Application to Autism Diagnosis using Cortical Morphological Networks. CoRR abs/2004.13321 (2020) - [i14]Markus D. Schirmer, Archana Venkataraman, Islem Rekik, Minjeong Kim, Stewart Mostofsky, Mary Beth Nebel, Keri Rosch, Karen Seymour, Deana Crocetti, Hassna Irzan, Michael Hütel, Sébastien 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:
Neuropsychiatric Disease Classification Using Functional Connectomics - Results of the Connectomics in NeuroImaging Transfer Learning Challenge. CoRR abs/2006.03611 (2020) - [i13]Mert Lostar, Islem Rekik:
Deep Hypergraph U-Net for Brain Graph Embedding and Classification. CoRR abs/2008.13118 (2020) - [i12]Islem Mhiri, Mohamed Ali Mahjoub, Islem Rekik:
Supervised Multi-topology Network Cross-diffusion for Population-driven Brain Network Atlas Estimation. CoRR abs/2009.11054 (2020) - [i11]Alaa Bessadok, Mohamed Ali Mahjoub, Islem Rekik:
Topology-Aware Generative Adversarial Network for Joint Prediction of Multiple Brain Graphs from a Single Brain Graph. CoRR abs/2009.11058 (2020) - [i10]Megi Isallari, Islem Rekik:
GSR-Net: Graph Super-Resolution Network for Predicting High-Resolution from Low-Resolution Functional Brain Connectomes. CoRR abs/2009.11080 (2020) - [i9]Ahmet Serkan Goktas, Alaa Bessadok, Islem Rekik:
Residual Embedding Similarity-Based Network Selection for Predicting Brain Network Evolution Trajectory from a Single Observation. CoRR abs/2009.11110 (2020) - [i8]Zeynep Gürler, Ahmed Nebli, Islem Rekik:
Foreseeing Brain Graph Evolution Over Time Using Deep Adversarial Network Normalizer. CoRR abs/2009.11166 (2020) - [i7]Ahmed Nebli, Islem Rekik:
Adversarial Brain Multiplex Prediction From a Single Network for High-Order Connectional Gender-Specific Brain Mapping. CoRR abs/2009.11524 (2020) - [i6]Mustafa Saglam, Islem Rekik:
Multi-Scale Profiling of Brain Multigraphs by Eigen-based Cross-Diffusion and Heat Tracing for Brain State Profiling. CoRR abs/2009.11534 (2020) - [i5]Alin Banka, Inis Buzi, Islem Rekik:
Multi-View Brain HyperConnectome AutoEncoder For Brain State Classification. CoRR abs/2009.11553 (2020) - [i4]Ahmed Nebli, Ugur Ali Kaplan, Islem Rekik:
Deep EvoGraphNet Architecture For Time-Dependent Brain Graph Data Synthesis From a Single Timepoint. CoRR abs/2009.13217 (2020) - [i3]Mustafa Burak Gurbuz, Islem Rekik:
Deep Graph Normalizer: A Geometric Deep Learning Approach for Estimating Connectional Brain Templates. CoRR abs/2012.14131 (2020)
2010 – 2019
- 2019
- [j17]Nesrine Bnouni, Islem Rekik, Mohamed Salah Rhim, Najoua Essoukri Ben Amara:
Cross-View Self-Similarity Using Shared Dictionary Learning for Cervical Cancer Staging. IEEE Access 7: 30079-30088 (2019) - [j16]Anna Lisowska, Islem Rekik:
Joint Pairing and Structured Mapping of Convolutional Brain Morphological Multiplexes for Early Dementia Diagnosis. Brain Connect. 9(1): 22-36 (2019) - [j15]Feng Zhao, Islem Rekik, Seong-Whan Lee, Jing Liu, Junying Zhang, Dinggang Shen:
Two-Phase Incremental Kernel PCA for Learning Massive or Online Datasets. Complex. 2019: 5937274:1-5937274:17 (2019) - [j14]Longwei Fang, Lichi Zhang, Dong Nie, Xiaohuan Cao, Islem Rekik, Seong-Whan Lee, Huiguang He, Dinggang Shen:
Automatic brain labeling via multi-atlas guided fully convolutional networks. Medical Image Anal. 51: 157-168 (2019) - [j13]Dingna Duan, Shunren Xia, Islem Rekik, Yu Meng, Zhengwang Wu, Li Wang, Weili Lin, John H. Gilmore, Dinggang Shen, Gang Li:
Exploring folding patterns of infant cerebral cortex based on multi-view curvature features: Methods and applications. NeuroImage 185: 575-592 (2019) - [j12]Gang Li, Li Wang, Pew-Thian Yap, Fan Wang, Zhengwang Wu, Yu Meng, Pei Dong, Jaeil Kim, Feng Shi, Islem Rekik, Weili Lin, Dinggang Shen:
Computational neuroanatomy of baby brains: A review. NeuroImage 185: 906-925 (2019) - [c37]Oumaima Ben Khelifa, Islem Rekik:
Graph Morphology-Based Genetic Algorithm for Classifying Late Dementia States. CNI@MICCAI 2019: 21-31 - [c36]Olfa Ghribi, Gang Li, Weili Lin, Dinggang Shen, Islem Rekik:
Progressive Infant Brain Connectivity Evolution Prediction from Neonatal MRI Using Bidirectionally Supervised Sample Selection. PRIME@MICCAI 2019: 63-72 - [c35]Alin Banka, Islem Rekik:
Adversarial Connectome Embedding for Mild Cognitive Impairment Identification Using Cortical Morphological Networks. CNI@MICCAI 2019: 74-82 - [c34]Mayssa Soussia, Islem Rekik:
7 Years of Developing Seed Techniques for Alzheimer's Disease Diagnosis Using Brain Image and Connectivity Data Largely Bypassed Prediction for Prognosis. PRIME@MICCAI 2019: 81-93 - [c33]Alaa Bessadok, Mohamed Ali Mahjoub, Islem Rekik:
Hierarchical Adversarial Connectomic Domain Alignment for Target Brain Graph Prediction and Classification from a Source Graph. PRIME@MICCAI 2019: 105-114 - [c32]Kübra Cengiz, Islem Rekik:
Predicting High-Resolution Brain Networks Using Hierarchically Embedded and Aligned Multi-resolution Neighborhoods. PRIME@MICCAI 2019: 115-124 - [c31]Alaa Bessadok, Mohamed Ali Mahjoub, Islem Rekik:
Symmetric Dual Adversarial Connectomic Domain Alignment for Predicting Isomorphic Brain Graph from a Baseline Graph. MICCAI (4) 2019: 465-474 - [c30]Baha Eddine Ezzine, Islem Rekik:
Learning-Guided Infinite Network Atlas Selection for Predicting Longitudinal Brain Network Evolution from a Single Observation. MICCAI (2) 2019: 796-805 - [e4]Islem Rekik, Ehsan Adeli, Sang Hyun Park:
Predictive Intelligence in Medicine - Second International Workshop, PRIME 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings. Lecture Notes in Computer Science 11843, Springer 2019, ISBN 978-3-030-32280-9 [contents] - [e3]Markus D. Schirmer, Archana Venkataraman, Islem Rekik, Minjeong Kim, Ai Wern Chung:
Connectomics in NeuroImaging - Third International Workshop, CNI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings. Lecture Notes in Computer Science 11848, Springer 2019, ISBN 978-3-030-32390-5 [contents] - [i2]Can Gafuroglu, Islem Rekik:
Image Evolution Trajectory Prediction and Classification from Baseline using Learning-based Patch Atlas Selection for Early Diagnosis. CoRR abs/1907.06064 (2019) - 2018
- [j11]Rory Raeper, Anna Lisowska, Islem Rekik:
Cooperative Correlational and Discriminative Ensemble Classifier Learning for Early Dementia Diagnosis Using Morphological Brain Multiplexes. IEEE Access 6: 43830-43839 (2018) - [j10]Mayssa Soussia, Islem Rekik:
Unsupervised Manifold Learning Using High-Order Morphological Brain Networks Derived From T1-w MRI for Autism Diagnosis. Frontiers Neuroinformatics 12: 70 (2018) - [j9]Samya Amiri, Mohamed Ali Mahjoub, Islem Rekik:
Tree-based Ensemble Classifier Learning for Automatic Brain Glioma Segmentation. Neurocomputing 313: 135-142 (2018) - [j8]Luping Zhou, Islem Rekik, Chenggang Yan, Guorong Wu:
Special Issue on High Performance Computing in Bio-medical Informatics. Neuroinformatics 16(3-4): 283 (2018) - [c29]Nesrine Bnouni, Olfa Mechi, Islem Rekik, Mohamed Salah Rhim, Najoua Essoukri Ben Amara:
Semi-automatic lymph node segmentation and classification using cervical cancer MR imaging. ATSIP 2018: 1-6 - [c28]Samya Amiri, Mohamed Ali Mahjoub, Islem Rekik:
Bayesian Network and Structured Random Forest Cooperative Deep Learning for Automatic Multi-label Brain Tumor Segmentation. ICAART (2) 2018: 183-190 - [c27]Islem Rekik, Gang Li, Weili Lin, Dinggang Shen:
Estimation of shape and growth brain network atlases for connectomic brain mapping in developing infants. ISBI 2018: 985-989 - [c26]Nesrine Bnouni, Islem Rekik, Mohamed Salah Rhim, Najoua Essoukri Ben Amara:
Dynamic Multi-scale CNN Forest Learning for Automatic Cervical Cancer Segmentation. MLMI@MICCAI 2018: 19-27 - [c25]Alaa Bessadok, Islem Rekik:
Intact Connectional Morphometricity Learning Using Multi-view Morphological Brain Networks with Application to Autism Spectrum Disorder. CNI@MICCAI 2018: 38-46 - [c24]Minghui Zhu, Islem Rekik:
Multi-view Brain Network Prediction from a Source View Using Sample Selection via CCA-Based Multi-kernel Connectomic Manifold Learning. PRIME@MICCAI 2018: 94-102 - [c23]Nicolas Georges, Islem Rekik:
Data-Specific Feature Selection Method Identification for Most Reproducible Connectomic Feature Discovery Fingerprinting Brain States. CNI@MICCAI 2018: 99-106 - [c22]Anna Lisowska, Islem Rekik:
Predicting Emotional Intelligence Scores from Multi-session Functional Brain Connectomes. PRIME@MICCAI 2018: 103-111 - [c21]Sophia Bano, Muhammad Asad, Ahmed E. Fetit, Islem Rekik:
XmoNet: A Fully Convolutional Network for Cross-Modality MR Image Inference. PRIME@MICCAI 2018: 129-137 - [c20]Can Gafuroglu, Islem Rekik, Alzheimer's Disease Neuroimaging Initiative:
Joint Prediction and Classification of Brain Image Evolution Trajectories from Baseline Brain Image with Application to Early Dementia. MICCAI (3) 2018: 437-445 - [c19]Islem Rekik, Gang Li, Weili Lin, Dinggang Shen:
Do Baby Brain Cortices that Look Alike at Birth Grow Alike During the First Year of Postnatal Development? MICCAI (3) 2018: 566-574 - [c18]Rory Raeper, Anna Lisowska, Islem Rekik:
Joint Correlational and Discriminative Ensemble Classifier Learning for Dementia Stratification Using Shallow Brain Multiplexes. MICCAI (1) 2018: 599-607 - [c17]Oualid M. Benkarim, Gerard Sanroma, Gemma Piella, Islem Rekik, Nadine Hahner, Elisenda Eixarch, Miguel Ángel González Ballester, Dinggang Shen, Gang Li:
Revealing Regional Associations of Cortical Folding Alterations with In Utero Ventricular Dilation Using Joint Spectral Embedding. MICCAI (3) 2018: 620-627 - [c16]Lichi Zhang, Han Zhang, Islem Rekik, Yaozong Gao, Qian Wang, Dinggang Shen:
Malignant Brain Tumor Classification Using the Random Forest Method. S+SSPR 2018: 14-21 - [c15]Samya Amiri, Mohamed Ali Mahjoub, Islem Rekik:
Dynamic Multiscale Tree Learning using Ensemble Strong Classifiers for Multi-label Segmentation of Medical Images with Lesions. VISIGRAPP (4: VISAPP) 2018: 419-426 - [e2]Guorong Wu, Islem Rekik, Markus D. Schirmer, Ai Wern Chung, Brent C. Munsell:
Connectomics in NeuroImaging - Second International Workshop, CNI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings. Lecture Notes in Computer Science 11083, Springer 2018, ISBN 978-3-030-00754-6 [contents] - [e1]Islem Rekik, Gözde B. Ünal, Ehsan Adeli, Sang Hyun Park:
PRedictive Intelligence in MEdicine - First International Workshop, PRIME 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings. Lecture Notes in Computer Science 11121, Springer 2018, ISBN 978-3-030-00319-7 [contents] - 2017
- [j7]Islem Rekik, Gang Li, Weili Lin, Dinggang Shen:
Erratum to "Predicting Infant Cortical Surface Development Using a 4D Varifold-based Learning Framework and Local Topography-based Shape Morphing" [Med. Image Anal. 28 (2016)1-12]. Medical Image Anal. 36: 1 (2017) - [j6]Islem Rekik, Gang Li, Pew-Thian Yap, Geng Chen, Weili Lin, Dinggang Shen:
Joint prediction of longitudinal development of cortical surfaces and white matter fibers from neonatal MRI. NeuroImage 152: 411-424 (2017) - [j5]Hongwei Wen, Yue Liu, Islem Rekik, Shengpei Wang, Zhiqiang Chen, Jishui Zhang, Yue Zhang, Yun Peng, Huiguang He:
Multi-modal multiple kernel learning for accurate identification of Tourette syndrome children. Pattern Recognit. 63: 601-611 (2017) - [c14]Islem Rekik, Gang Li, Weili Lin, Dinggang Shen:
Estimation of Brain Network Atlases Using Diffusive-Shrinking Graphs: Application to Developing Brains. IPMI 2017: 385-397 - [c13]Dingna Duan, Islem Rekik, Shunren Xia, Weili Lin, John H. Gilmore, Dinggang Shen, Gang Li:
Longitudinal multi-scale mapping of infant cortical folding using spherical wavelets. ISBI 2017: 93-96 - [c12]Carrie Morris, Islem Rekik:
Autism Spectrum Disorder Diagnosis Using Sparse Graph Embedding of Morphological Brain Networks. GRAIL/MFCA/MICGen@MICCAI 2017: 12-20 - [c11]Anna Lisowska, Islem Rekik:
Pairing-based Ensemble Classifier Learning using Convolutional Brain Multiplexes and Multi-view Brain Networks for Early Dementia Diagnosis. CNI@MICCAI 2017: 42-50 - [c10]Mayssa Soussia, Islem Rekik:
High-order Connectomic Manifold Learning for Autistic Brain State Identification. CNI@MICCAI 2017: 51-59 - [c9]Khosro Bahrami, Islem Rekik, Feng Shi, Dinggang Shen:
Joint Reconstruction and Segmentation of 7T-like MR Images from 3T MRI Based on Cascaded Convolutional Neural Networks. MICCAI (1) 2017: 764-772 - [i1]Samya Amiri, Mohamed Ali Mahjoub, Islem Rekik:
Dynamic Multiscale Tree Learning Using Ensemble Strong Classifiers for Multi-label Segmentation of Medical Images with Lesions. CoRR abs/1709.01602 (2017) - 2016
- [j4]Islem Rekik, Gang Li, Weili Lin, Dinggang Shen:
Predicting infant cortical surface development using a 4D varifold-based learning framework and local topography-based shape morphing. Medical Image Anal. 28: 1-12 (2016) - [j3]Islem Rekik, Gang Li, Weili Lin, Dinggang Shen:
Multidirectional and Topography-based Dynamic-scale Varifold Representations with Application to Matching Developing Cortical Surfaces. NeuroImage 135: 152-162 (2016) - [c8]Samya Amiri, Islem Rekik, Mohamed Ali Mahjoub:
Deep random forest-based learning transfer to SVM for brain tumor segmentation. ATSIP 2016: 297-302 - [c7]Luyan Liu, Han Zhang, Islem Rekik, Xiaobo Chen, Qian Wang, Dinggang Shen:
Outcome Prediction for Patient with High-Grade Gliomas from Brain Functional and Structural Networks. MICCAI (2) 2016: 26-34 - [c6]Khosro Bahrami, Feng Shi, Islem Rekik, Dinggang Shen:
Convolutional Neural Network for Reconstruction of 7T-like Images from 3T MRI Using Appearance and Anatomical Features. LABELS/DLMIA@MICCAI 2016: 39-47 - [c5]Islem Rekik, Gang Li, Pew-Thian Yap, Geng Chen, Weili Lin, Dinggang Shen:
A Hybrid Multishape Learning Framework for Longitudinal Prediction of Cortical Surfaces and Fiber Tracts Using Neonatal Data. MICCAI (1) 2016: 210-218 - [c4]Khosro Bahrami, Islem Rekik, Feng Shi, Yaozong Gao, Dinggang Shen:
7T-Guided Learning Framework for Improving the Segmentation of 3T MR Images. MICCAI (2) 2016: 572-580 - 2015
- [c3]Islem Rekik, Gang Li, Weili Lin, Dinggang Shen:
Prediction of Longitudinal Development of Infant Cortical Surface Shape Using a 4D Current-Based Learning Framework. IPMI 2015: 576-587 - [c2]Islem Rekik, Gang Li, Guorong Wu, Weili Lin, Dinggang Shen:
Prediction of Infant MRI Appearance and Anatomical Structure Evolution Using Sparse Patch-Based Metamorphosis Learning Framework. Patch-MI@MICCAI 2015: 197-204 - [c1]Islem Rekik, Gang Li, Weili Lin, Dinggang Shen:
Topography-Based Registration of Developing Cortical Surfaces in Infants Using Multidirectional Varifold Representation. MICCAI (2) 2015: 230-237 - 2013
- [j2]Islem Rekik, Stéphanie Allassonnière, Stanley Durrleman, Trevor Carpenter, Joanna M. Wardlaw:
Spatiotemporal Dynamic Simulation of Acute Perfusion/Diffusion Ischemic Stroke Lesions Evolution: A Pilot Study Derived from Longitudinal MR Patient Data. Comput. Math. Methods Medicine 2013: 283593:1-283593:13 (2013) - [j1]Islem Rekik, Stéphanie Allassonnière, Olivier Clatz, Ezequiel Geremia, Erin Stretton, Hervé Delingette, Nicholas Ayache:
Tumor growth parameters estimation and source localization from a unique time point: Application to low-grade gliomas. Comput. Vis. Image Underst. 117(3): 238-249 (2013)
Coauthor Index
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