| Multi-scale convolutional neural networks for lung nodule classification W Shen, M Zhou, F Yang, C Yang, J Tian International Conference on Information Processing in Medical Imaging, 588-599, 2015 | 764 | 2015 |
| Multi-crop convolutional neural networks for lung nodule malignancy suspiciousness classification W Shen, M Zhou, F Yang, D Yu, D Dong, C Yang, Y Zang, J Tian Pattern Recognition 61, 663-673, 2017 | 666 | 2017 |
| Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation S Wang, M Zhou, Z Liu, Z Liu, D Gu, Y Zang, D Dong, O Gevaert, J Tian Medical image analysis 40, 172-183, 2017 | 495 | 2017 |
| UTNet: a hybrid transformer architecture for medical image segmentation Y Gao, M Zhou, DN Metaxas International Conference on Medical Image Computing and Computer-Assisted …, 2021 | 492 | 2021 |
| Radiomics in Brain Tumor: Image Assessment, Quantitative Feature Descriptors, and Machine-Learning Approaches M Zhou, J Scott, B Chaudhury, L Hall, D Goldgof, KW Yeom, M Iv, Y Ou, ... American Journal of Neuroradiology, 2017 | 384 | 2017 |
| Predicting EGFR mutation status in lung adenocarcinoma on computed tomography image using deep learning S Wang, J Shi, Z Ye, D Dong, D Yu, M Zhou, Y Liu, O Gevaert, K Wang, ... European Respiratory Journal 53 (3), 1800986, 2019 | 378 | 2019 |
| A radiogenomic dataset of non-small cell lung cancer S Bakr, O Gevaert, S Echegaray, K Ayers, M Zhou, M Shafiq, H Zheng, ... Scientific data 5 (1), 1-9, 2018 | 257 | 2018 |
| Non–small cell lung cancer radiogenomics map identifies relationships between molecular and imaging phenotypes with prognostic implications M Zhou, A Leung, S Echegaray, A Gentles, JB Shrager, KC Jensen, ... Radiology 286 (1), 307, 2018 | 192 | 2018 |
| DeepCDR: a hybrid graph convolutional network for predicting cancer drug response Q Liu, Z Hu, R Jiang, M Zhou Bioinformatics 36, i911-i918, 2020 | 160 | 2020 |
| A multi-view deep convolutional neural networks for lung nodule segmentation S Wang, M Zhou, O Gevaert, Z Tang, D Dong, Z Liu, J Tian 2017 39th Annual International Conference of the IEEE Engineering in …, 2017 | 132 | 2017 |
| Facial action unit recognition with sparse representation MH Mahoor, M Zhou, KL Veon, SM Mavadati, JF Cohn Automatic Face & Gesture Recognition and Workshops (FG 2011), 2011 IEEE …, 2011 | 114 | 2011 |
| MR imaging–based radiomic signatures of distinct molecular subgroups of medulloblastoma M Iv, M Zhou, K Shpanskaya, S Perreault, Z Wang, E Tranvinh, ... American Journal of Neuroradiology 40 (1), 154-161, 2019 | 113 | 2019 |
| Radiologically defined ecological dynamics and clinical outcomes in glioblastoma multiforme: preliminary results M Zhou, L Hall, D Goldgof, R Russo, Y Balagurunathan, R Gillies, ... Translational oncology 7 (1), 5-13, 2014 | 109 | 2014 |
| Learning from Experts: Developing Transferable Deep Features for Patient-Level Lung Cancer Prediction W Shen, M Zhou, F Yang, D Dong, C Yang, Y Zang, J Tian International Conference on Medical Image Computing and Computer-Assisted …, 2016 | 94 | 2016 |
| A data-scalable transformer for medical image segmentation: architecture, model efficiency, and benchmark Y Gao, M Zhou, D Liu, Z Yan, S Zhang, DN Metaxas arXiv preprint arXiv:2203.00131, 2022 | 93 | 2022 |
| Identifying spatial imaging biomarkers of glioblastoma multiforme for survival group prediction M Zhou, B Chaudhury, LO Hall, DB Goldgof, RJ Gillies, RA Gatenby Journal of Magnetic Resonance Imaging, 2016 | 92 | 2016 |
| A shallow convolutional neural network predicts prognosis of lung cancer patients in multi-institutional computed tomography image datasets P Mukherjee, M Zhou, E Lee, A Schicht, Y Balagurunathan, S Napel, ... Nature machine intelligence 2 (5), 274-282, 2020 | 89 | 2020 |
| Development and validation of radiomic signatures of head and neck squamous cell carcinoma molecular features and subtypes C Huang, M Cintra, K Brennan, M Zhou, AD Colevas, N Fischbein, S Zhu, ... EBioMedicine 45, 70-80, 2019 | 88 | 2019 |
| Genetic mutation and biological pathway prediction based on whole slide images in breast carcinoma using deep learning H Qu, M Zhou, Z Yan, H Wang, VK Rustgi, S Zhang, O Gevaert, ... NPJ precision oncology 5 (1), 87, 2021 | 80 | 2021 |
| Toward heterogeneous information fusion: bipartite graph convolutional networks for in silico drug repurposing Z Wang, M Zhou, C Arnold Bioinformatics 36 (Supplement_1), i525-i533, 2020 | 79 | 2020 |
Olivier GevaertStanford UniversityVerified email at stanford.edu
