| A review: Deep learning for medical image segmentation using multi-modality fusion T Zhou, S Ruan, S Canu Array 3, 100004, 2019 | 615 | 2019 |
| Automatic COVID‐19 CT segmentation using U‐Net integrated spatial and channel attention mechanism T Zhou, S Canu, S Ruan International Journal of Imaging Systems and Technology 31 (1), 16-27, 2021 | 196 | 2021 |
| Latent correlation representation learning for brain tumor segmentation with missing MRI modalities T Zhou, S Canu, P Vera, S Ruan IEEE Transactions on Image Processing 30, 4263-4274, 2021 | 168 | 2021 |
| A multi-modality fusion network based on attention mechanism for brain tumor segmentation T Zhou, S Ruan, Y Guo, S Canu 2020 IEEE 17th international symposium on biomedical imaging (ISBI), 377-380, 2020 | 64 | 2020 |
| An automatic COVID-19 CT segmentation network using spatial and channel attention mechanism T Zhou, S Canu, S Ruan arXiv preprint arXiv:2004.06673, 2020 | 54 | 2020 |
| A Tri-Attention fusion guided multi-modal segmentation network T Zhou, S Ruan, P Vera, S Canu Pattern Recognition 124, 108417, 2022 | 45 | 2022 |
| Brain tumor segmentation with missing modalities via latent multi-source correlation representation T Zhou, S Canu, P Vera, S Ruan Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 …, 2020 | 44 | 2020 |
| Fusion based on attention mechanism and context constraint for multi-modal brain tumor segmentation T Zhou, S Canu, S Ruan Computerized Medical Imaging and Graphics 86, 101811, 2020 | 40 | 2020 |
| Feature-enhanced generation and multi-modality fusion based deep neural network for brain tumor segmentation with missing MR modalities T Zhou, S Canu, P Vera, S Ruan Neurocomputing 466, 102-112, 2021 | 38 | 2021 |
| Lymphoma segmentation in PET images based on multi-view and Conv3D fusion strategy H Hu, L Shen, T Zhou, P Decazes, P Vera, S Ruan 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1197-1200, 2020 | 19 | 2020 |
| Scale adaptive kernelized correlation filter tracker with feature fusion T Zhou, M Zhu, D Zeng, H Yang Mathematical Problems in Engineering 2017 (1), 1605959, 2017 | 18 | 2017 |
| A literature survey of MR-based brain tumor segmentation with missing modalities T Zhou, S Ruan, H Hu Computerized Medical Imaging and Graphics 104, 102167, 2023 | 16 | 2023 |
| 3d medical multi-modal segmentation network guided by multi-source correlation constraint T Zhou, S Canu, P Vera, S Ruan 2020 25th International Conference on Pattern Recognition (ICPR), 10243-10250, 2021 | 16 | 2021 |
| A review: Deep learning for medical image segmentation using multi-modality fusion. Array 3–4, 100004 T Zhou, S Ruan, S Canu | 16 | 2019 |
| Missing data imputation via conditional generator and correlation learning for multimodal brain tumor segmentation T Zhou, P Vera, S Canu, S Ruan Pattern Recognition Letters 158, 125-132, 2022 | 14 | 2022 |
| Modality-level cross-connection and attentional feature fusion based deep neural network for multi-modal brain tumor segmentation T Zhou Biomedical Signal Processing and Control 81, 104524, 2023 | 13 | 2023 |
| Extended scale invariant local binary pattern for background subtraction D Zeng, M Zhu, F Xu, T Zhou IET Image Processing 12 (8), 1292-1302, 2018 | 12 | 2018 |
| Deep learning model integrating dilated convolution and deep supervision for brain tumor segmentation in multi-parametric mri T Zhou, S Ruan, H Hu, S Canu Machine Learning in Medical Imaging: 10th International Workshop, MLMI 2019 …, 2019 | 10 | 2019 |
| Uncertainty quantification and attention-aware fusion guided multi-modal MR brain tumor segmentation T Zhou, S Zhu Computers in Biology and Medicine 163, 107142, 2023 | 9 | 2023 |
| Feature fusion and latent feature learning guided brain tumor segmentation and missing modality recovery network T Zhou Pattern Recognition 141, 109665, 2023 | 9 | 2023 |
Stéphane CanuProfessor of Data Science, INSA RouenVerified email at insa-rouen.fr
