| Identification of COVID-19 samples from chest X-Ray images using deep learning: A comparison of transfer learning approaches MM Rahaman, C Li, Y Yao, F Kulwa, MA Rahman, Q Wang, S Qi, F Kong, ... Journal of X-ray Science and Technology 28 (5), 821-839, 2020 | 355 | 2020 |
| GasHis-Transformer: A multi-scale visual transformer approach for gastric histopathological image detection H Chen, C Li, G Wang, X Li, MM Rahaman, H Sun, W Hu, Y Li, W Liu, ... Pattern Recognition 130, 108827, 2022 | 224* | 2022 |
| DeepCervix: a deep learning-based framework for the classification of cervical cells using hybrid deep feature fusion techniques MM Rahaman, C Li, Y Yao, F Kulwa, X Wu, X Li, Q Wang Computers in Biology and Medicine 136, 104649, 2021 | 219 | 2021 |
| A comprehensive review of computer-aided whole-slide image analysis: from datasets to feature extraction, segmentation, classification and detection approaches X Li, C Li, MM Rahaman, H Sun, X Li, J Wu, Y Yao, M Grzegorzek Artificial Intelligence Review 55 (6), 4809-4878, 2022 | 215 | 2022 |
| A comprehensive review for breast histopathology image analysis using classical and deep neural networks X Zhou, C Li, MM Rahaman, Y Yao, S Ai, C Sun, Q Wang, Y Zhang, M Li, ... IEEE Access 8, 90931-90956, 2020 | 197 | 2020 |
| CVM-Cervix: A Hybrid Cervical Pap-Smear Image Classification Framework Using CNN, Visual Transformer and Multilayer Perceptron W Liu, C Li, N Xu, T Jiang, MM Rahaman, H Sun, X Wu, W Hu, H Chen, ... Pattern Recognition, 108829, 2022 | 159 | 2022 |
| A comprehensive review of image analysis methods for microorganism counting: from classical image processing to deep learning approaches J Zhang, C Li, MM Rahaman, Y Yao, P Ma, J Zhang, X Zhao, T Jiang, ... Artificial Intelligence Review, 1-70, 2022 | 147 | 2022 |
| An application of transfer learning and ensemble learning techniques for cervical histopathology image classification D Xue, X Zhou, C Li, Y Yao, MM Rahaman, J Zhang, H Chen, J Zhang, ... IEEE Access 8, 104603-104618, 2020 | 140 | 2020 |
| A survey for cervical cytopathology image analysis using deep learning MM Rahaman, C Li, X Wu, Y Yao, Z Hu, T Jiang, X Li, S Qi IEEE Access 8, 61687-61710, 2020 | 138 | 2020 |
| IL-MCAM: An interactive learning and multi-channel attention mechanism-based weakly supervised colorectal histopathology image classification approach H Chen, C Li, X Li, MM Rahaman, W Hu, Y Li, W Liu, C Sun, H Sun, ... Computers in Biology and Medicine 143, 105265, 2022 | 110 | 2022 |
| A state-of-the-art survey of object detection techniques in microorganism image analysis: from classical methods to deep learning approaches P Ma, C Li, MM Rahaman, Y Yao, J Zhang, S Zou, X Zhao, M Grzegorzek Artificial Intelligence Review 56 (2), 1627-1698, 2023 | 82 | 2023 |
| GasHisSDB: A new gastric histopathology image dataset for computer aided diagnosis of gastric cancer W Hu, C Li, X Li, MM Rahaman, J Ma, Y Zhang, H Chen, W Liu, C Sun, ... Computers in biology and medicine 142, 105207, 2022 | 78 | 2022 |
| SVIA dataset: a new dataset of microscopic videos and images for computer-aided sperm analysis A Chen, C Li, S Zou, MM Rahaman, Y Yao, H Chen, H Yang, P Zhao, ... Biocybernetics and Biomedical Engineering 42 (1), 204-214, 2022 | 76 | 2022 |
| Is the aspect ratio of cells important in deep learning? A robust comparison of deep learning methods for multi-scale cytopathology cell image classification: From … W Liu, C Li, MM Rahaman, T Jiang, H Sun, X Wu, W Hu, H Chen, C Sun, ... Computers in biology and medicine 141, 105026, 2022 | 69 | 2022 |
| A comprehensive review of Markov random field and conditional random field approaches in pathology image analysis Y Li, C Li, X Li, K Wang, MM Rahaman, C Sun, H Chen, X Wu, H Zhang, ... Archives of Computational Methods in Engineering 29 (1), 609-639, 2022 | 59 | 2022 |
| A Comparison of Deep Learning Classification Methods on a Small Environmental Microorganism Image Dataset (EMDS-6): from Convolutional Neural Networks to Visual Transformers P Zhao, C Li, MM Rahaman, H Xu, H Yang, H Sun, T Jiang, M Grzegorzek Frontiers in Microbiology, 473, 2022 | 50* | 2022 |
| Gastric histopathology image segmentation using a hierarchical conditional random field C Sun, C Li, J Zhang, MM Rahaman, S Ai, H Chen, F Kulwa, Y Li, X Li, ... Biocybernetics and Biomedical Engineering 40 (4), 1535-1555, 2020 | 50 | 2020 |
| An enhanced framework of generative adversarial networks (EF-GANs) for environmental microorganism image augmentation with limited rotation-invariant training data H Xu, C Li, MM Rahaman, Y Yao, Z Li, J Zhang, F Kulwa, X Zhao, S Qi, ... IEEE Access 8, 187455-187469, 2020 | 44 | 2020 |
| A State‐of‐the‐Art Review for Gastric Histopathology Image Analysis Approaches and Future Development S Ai, C Li, X Li, T Jiang, M Grzegorzek, C Sun, MM Rahaman, J Zhang, ... BioMed Research International 2021 (1), 6671417, 2021 | 42 | 2021 |
| A hierarchical conditional random field-based attention mechanism approach for gastric histopathology image classification Y Li, X Wu, C Li, X Li, H Chen, C Sun, MM Rahaman, Y Yao, Y Zhang, ... Applied Intelligence, 1-22, 2022 | 34 | 2022 |
Chen LiNortheastern University, ChinaE-mail megerősítve itt: bmie.neu.edu.cn
