| Diagnosis of autism spectrum disorders using multi-level high-order functional networks derived from resting-state functional mri F Zhao, H Zhang, I Rekik, Z An, D Shen Frontiers in human neuroscience 12, 184, 2018 | 157 | 2018 |
| Medical image analysis methods in MR/CT-imaged acute-subacute ischemic stroke lesion: Segmentation, prediction and insights into dynamic evolution simulation models. A critical … I Rekik, S Allassonnière, TK Carpenter, JM Wardlaw NeuroImage: Clinical 1 (1), 164-178, 2012 | 117 | 2012 |
| Convolutional neural network for reconstruction of 7T-like images from 3T MRI using appearance and anatomical features K Bahrami, F Shi, I Rekik, D Shen Deep Learning and Data Labeling for Medical Applications, 39-47, 2016 | 92 | 2016 |
| Computational neuroanatomy of baby brains: A review G Li, L Wang, PT Yap, F Wang, Z Wu, Y Meng, P Dong, J Kim, F Shi, ... NeuroImage 185, 906-925, 2019 | 61 | 2019 |
| Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states I Mahjoub, MA Mahjoub, I Rekik Scientific reports 8 (1), 1-14, 2018 | 46 | 2018 |
| Tumor growth parameters estimation and source localization from a unique time point: Application to low-grade gliomas I Rekik, S Allassonnière, O Clatz, E Geremia, E Stretton, H Delingette, ... Computer Vision and Image Understanding 117 (3), 238-249, 2013 | 37 | 2013 |
| Outcome prediction for patient with high-grade gliomas from brain functional and structural networks L Liu, H Zhang, I Rekik, X Chen, Q Wang, D Shen International Conference on Medical Image Computing and Computer-Assisted …, 2016 | 33 | 2016 |
| Unsupervised Manifold Learning Using High-Order Morphological Brain Networks Derived From T1-w MRI for Autism Diagnosis M Soussia, I Rekik Frontiers in Neuroinformatics 12 (https://www.frontiersin.org/articles/10.), 70, 2018 | 31 | 2018 |
| Joint pairing and structured mapping of convolutional brain morphological multiplexes for early dementia diagnosis A Lisowska, I Rekik, AbbVie, Alzheimer's Association, ... Brain connectivity 9 (1), 22-36, 2019 | 29 | 2019 |
| Joint reconstruction and segmentation of 7T-like MR images from 3T MRI based on cascaded convolutional neural networks K Bahrami, I Rekik, F Shi, D Shen International Conference on Medical Image Computing and Computer-Assisted …, 2017 | 25 | 2017 |
| Combining tract‐and atlas‐based analysis reveals microstructural abnormalities in early Tourette syndrome children H Wen, Y Liu, J Wang, I Rekik, J Zhang, Y Zhang, H Tian, Y Peng, H He Human brain mapping 37 (5), 1903-1919, 2016 | 25 | 2016 |
| 7T‐guided super‐resolution of 3T MRI K Bahrami, F Shi, I Rekik, Y Gao, D Shen Medical physics 44 (5), 1661-1677, 2017 | 22 | 2017 |
| Predicting infant cortical surface development using a 4D varifold-based learning framework and local topography-based shape morphing I Rekik, G Li, W Lin, D Shen Medical image analysis 28, 1-12, 2016 | 21 | 2016 |
| High-order connectomic manifold learning for autistic brain state identification M Soussia, I Rekik International Workshop on Connectomics in Neuroimaging, 51-59, 2017 | 20 | 2017 |
| Pairing-based ensemble classifier learning using convolutional brain multiplexes and multi-view brain networks for early dementia diagnosis A Lisowska, I Rekik, Alzheimers Disease Neuroimaging Initiative International Workshop on Connectomics in Neuroimaging, 42-50, 2017 | 18 | 2017 |
| Gender differences in cortical morphological networks A Nebli, I Rekik Brain imaging and behavior 14 (5), 1831-1839, 2020 | 17 | 2020 |
| Combining disrupted and discriminative topological properties of functional connectivity networks as neuroimaging biomarkers for accurate diagnosis of early tourette syndrome … H Wen, Y Liu, I Rekik, S Wang, Z Chen, J Zhang, Y Zhang, Y Peng, H He Molecular neurobiology 55 (4), 3251-3269, 2018 | 17 | 2018 |
| Deep random forest-based learning transfer to SVM for brain tumor segmentation S Amiri, I Rekik, MA Mahjoub 2016 2nd International Conference on Advanced Technologies for Signal and …, 2016 | 16 | 2016 |
| Clustering-based multi-view network fusion for estimating brain network atlases of healthy and disordered populations S Dhifallah, I Rekik, Alzheimer's Disease Neuroimaging Initiative Journal of neuroscience methods 311, 426-435, 2019 | 15 | 2019 |
| Multi-modal multiple kernel learning for accurate identification of Tourette syndrome children H Wen, Y Liu, I Rekik, S Wang, Z Chen, J Zhang, Y Zhang, Y Peng, H He Pattern Recognition 63, 601-611, 2017 | 15 | 2017 |
Dinggang ShenProfessor and Dean, School of BME, ShanghaiTech University; Co-CEO, United Imaging IntelligenceVerified email at shanghaitech.edu.cn
