| The role of imaging in the detection and management of COVID-19: a review D Dong, Z Tang, S Wang, H Hui, L Gong, Y Lu, Z Xue, H Liao, F Chen, ... IEEE reviews in biomedical engineering 14, 16-29, 2020 | 417 | 2020 |
| Non-invasive decision support for NSCLC treatment using PET/CT radiomics W Mu, L Jiang, JY Zhang, Y Shi, JE Gray, I Tunali, C Gao, Y Sun, J Tian, ... Nature communications 11 (1), 5228, 2020 | 168 | 2020 |
| Quantitative imaging of cancer in the postgenomic era: Radio (geno) mics, deep learning, and habitats S Napel, W Mu, BV Jardim‐Perassi, HJWL Aerts, RJ Gillies Cancer 124 (24), 4633-4649, 2018 | 153 | 2018 |
| Radiomics of 18 F-FDG PET/CT images predicts clinical benefit of advanced NSCLC patients to checkpoint blockade immunotherapy W Mu, I Tunali, JE Gray, J Qi, MB Schabath, RJ Gillies European journal of nuclear medicine and molecular imaging 47 (5), 1168-1182, 2020 | 142 | 2020 |
| Non-invasive measurement of PD-L1 status and prediction of immunotherapy response using deep learning of PET/CT images W Mu, L Jiang, Y Shi, I Tunali, JE Gray, E Katsoulakis, J Tian, RJ Gillies, ... Journal for Immunotherapy of Cancer 9 (6), 2021 | 101 | 2021 |
| Staging of cervical cancer based on tumor heterogeneity characterized by texture features on 18F-FDG PET images W Mu, Z Chen, Y Liang, W Shen, F Yang, R Dai, N Wu, J Tian Physics in Medicine & Biology 60 (13), 5123, 2015 | 92 | 2015 |
| Assessing PD-L1 expression in non-small cell lung cancer and predicting responses to immune checkpoint inhibitors using deep learning on computed tomography images P Tian, B He, W Mu, K Liu, L Liu, H Zeng, Y Liu, L Jiang, P Zhou, Z Huang, ... Theranostics 11 (5), 2098, 2021 | 80 | 2021 |
| Improving survival prediction of high-grade glioma via machine learning techniques based on MRI radiomic, genetic and clinical risk factors Y Tan, W Mu, X Wang, G Yang, RJ Gillies, H Zhang European journal of radiology 120, 108609, 2019 | 53 | 2019 |
| A Non-invasive Radiomic Method Using 18F-FDG PET Predicts Isocitrate Dehydrogenase Genotype and Prognosis in Patients with Glioma L Li, W Mu, Z Liu, Z Liu, Y Wang, W Ma, Z Kong, S Wang, W Wei, X Cheng, ... Frontiers in Oncology 9, 1183, 2019 | 44 | 2019 |
| Integrating manual diagnosis into radiomics for reducing the false positive rate of 18F-FDG PET/CT diagnosis in patients with suspected lung cancer F Kang, W Mu, J Gong, S Wang, G Li, G Li, W Qin, J Tian, J Wang European Journal of Nuclear Medicine and Molecular Imaging 46 (13), 2770-2779, 2019 | 37 | 2019 |
| Radiomics of 18F Fluorodeoxyglucose PET/CT Images Predicts Severe Immune-related Adverse Events in Patients with NSCLC W Mu, I Tunali, J Qi, MB Schabath, RJ Gillies Radiology: Artificial Intelligence 2 (1), e190063, 2020 | 30 | 2020 |
| Radiomics predicts risk of cachexia in advanced NSCLC patients treated with immune checkpoint inhibitors W Mu, E Katsoulakis, CJ Whelan, KL Gage, MB Schabath, RJ Gillies British Journal of Cancer 125 (2), 229-239, 2021 | 26 | 2021 |
| A Segmentation Algorithm for Quantitative Analysis of Heterogeneous Tumors of the Cervix With 18 F-FDG PET/CT W Mu, Z Chen, W Shen, F Yang, Y Liang, R Dai, N Wu, J Tian IEEE Transactions on Biomedical Engineering 62 (10), 2465-2479, 2015 | 26 | 2015 |
| Multi-window CT based Radiomic signatures in differentiating indolent versus aggressive lung cancers in the National Lung Screening Trial: a retrospective study H Lu, W Mu, Y Balagurunathan, J Qi, MA Abdalah, AL Garcia, Z Ye, ... Cancer Imaging 19 (1), 45, 2019 | 25 | 2019 |
| Radiomic biomarkers from PET/CT multi-modality fusion images for the prediction of immunotherapy response in advanced non-small cell lung cancer patients W Mu, J Qi, H Lu, M Schabath, Y Balagurunathan, I Tunali, RJ Gillies Medical Imaging 2018: Computer-Aided Diagnosis 10575, 854-860, 2018 | 24 | 2018 |
| Automatic localization of vertebrae based on convolutional neural networks W Shen, F Yang, W Mu, C Yang, X Yang, J Tian Medical Imaging 2015: Image Processing 9413, 94132E, 2015 | 23 | 2015 |
| 18F-FDG PET/CT Habitat Radiomics Predicts Outcome of Patients with Cervical Cancer Treated with Chemoradiotherapy W Mu, Y Liang, LO Hall, Y Tan, Y Balagurunathan, R Wenham, N Wu, ... Radiology: Artificial Intelligence 2 (6), e190218, 2020 | 22 | 2020 |
| Prediction of clinically relevant Pancreatico-enteric Anastomotic Fistulas after Pancreatoduodenectomy using deep learning of Preoperative Computed Tomography W Mu, C Liu, F Gao, Y Qi, H Lu, Z Liu, X Zhang, X Cai, RY Ji, Y Hou, ... Theranostics 10 (21), 9779, 2020 | 21 | 2020 |
| Images Are Data: Challenges and Opportunities in the Clinical Translation of Radiomics W Mu, MB Schabath, RJ Gillies Cancer Research 82 (11), 2066-2068, 2022 | 18 | 2022 |
| Deep-learning and MR images to target hypoxic habitats with evofosfamide in preclinical models of sarcoma BV Jardim-Perassi, W Mu, S Huang, MR Tomaszewski, J Poleszczuk, ... Theranostics 11 (11), 5313-5329, 2021 | 12 | 2021 |
