Cascade of multi-scale convolutional neural networks for bone suppression of chest radiographs in gradient domain W Yang, Y Chen, Y Liu, L Zhong, G Qin, Z Lu, Q Feng, W Chen Medical image analysis 35, 421-433, 2017 | 147 | 2017 |
Magnesium levels in drinking water and coronary heart disease mortality risk: a meta-analysis L Jiang, P He, J Chen, Y Liu, D Liu, G Qin, N Tan Nutrients 8 (1), 5, 2016 | 91 | 2016 |
Predicting the molecular subtype of breast cancer and identifying interpretable imaging features using machine learning algorithms M Ma, R Liu, C Wen, W Xu, Z Xu, S Wang, J Wu, D Pan, B Zheng, G Qin, ... European Radiology, 1-11, 2022 | 55 | 2022 |
Digital breast tomosynthesis versus digital mammography: integration of image modalities enhances deep learning-based breast mass classification X Li, G Qin, Q He, L Sun, H Zeng, Z He, W Chen, X Zhen, L Zhou European radiology 30, 778-788, 2020 | 54 | 2020 |
OXPHOS-dependent metabolic reprogramming prompts metastatic potential of breast cancer cells under osteogenic differentiation Y Hu, W Xu, H Zeng, Z He, X Lu, D Zuo, G Qin, W Chen British Journal of Cancer 123 (11), 1644-1655, 2020 | 34 | 2020 |
Multi-objective based radiomic feature selection for lesion malignancy classification JW Zhiguo Zhou, Shulong Li, Genggeng Qin, Michael Folkert, Steve Jiang IEEE journal of biomedical and health informatics, 2019 | 32 | 2019 |
Synthesis of mammogram from digital breast tomosynthesis using deep convolutional neural network with gradient guided cGANs G Jiang, J Wei, Y Xu, Z He, H Zeng, J Wu, G Qin, W Chen, Y Lu IEEE Transactions on Medical Imaging 40 (8), 2080-2091, 2021 | 31 | 2021 |
Head and neck osteosarcoma: CT and MR imaging features Z Luo, W Chen, X Shen, G Qin, J Yuan, B Hu, J Lyu, C Wen, W Xu Dentomaxillofacial Radiology 49 (2), 20190202, 2020 | 27 | 2020 |
The mammography and MRI manifestations of adenomyoepithelioma of the breast L Zhang, G Qin, Z He, W Chen, L Yang Clinical Radiology 71 (3), 235-243, 2016 | 24 | 2016 |
A deep learning–machine learning fusion approach for the classification of benign, malignant, and intermediate bone tumors R Liu, D Pan, Y Xu, H Zeng, Z He, J Lin, W Zeng, Z Wu, Z Luo, G Qin, ... European Radiology 32 (2), 1371-1383, 2022 | 23 | 2022 |
Bone suppression of chest radiographs with cascaded convolutional networks in wavelet domain Y Chen, X Gou, X Feng, Y Liu, G Qin, Q Feng, W Yang, W Chen IEEE Access 7, 8346-8357, 2019 | 23 | 2019 |
Cathepsin L is involved in proliferation and invasion of breast cancer cells G Qin, Y Cai, J Long, H Zeng, W Xu, Y Li, M Liu, H Zhang, ZL He, ... Neoplasma 63 (1), 30-36, 2016 | 20 | 2016 |
An interpretable model‐based prediction of severity and crucial factors in patients with COVID‐19 B Zheng, Y Cai, F Zeng, M Lin, J Zheng, W Chen, G Qin, Y Guo BioMed Research International 2021 (1), 8840835, 2021 | 19 | 2021 |
Deep learning of mammary gland distribution for architectural distortion detection in digital breast tomosynthesis Y Li, Z He, Y Lu, X Ma, Y Guo, Z Xie, G Qin, W Xu, Z Xu, W Chen, H Chen Physics in Medicine & Biology 66 (3), 035028, 2021 | 18 | 2021 |
A multiscale contrast enhancement for mammogram using dynamic unsharp masking in Laplacian pyramid X Duan, Y Mei, S Wu, Q Ling, G Qin, J Ma, C Chen, H Qi, L Zhou, Y Xu IEEE transactions on radiation and plasma medical sciences 3 (5), 557-564, 2018 | 18 | 2018 |
Extraskeletal myxoid chondrosarcoma: a comparative study of imaging and pathology L Zhang, R Wang, R Xu, G Qin, L Yang BioMed research international 2018 (1), 9684268, 2018 | 16 | 2018 |
Predicting futile recanalization, malignant cerebral edema, and cerebral herniation using intelligible ensemble machine learning following mechanical thrombectomy for acute … W Zeng, W Li, K Huang, Z Lin, H Dai, Z He, R Liu, Z Zeng, G Qin, W Chen, ... Frontiers in Neurology 13, 982783, 2022 | 13 | 2022 |
CT and MRI features of calvarium and skull base osteosarcoma (CSBO) Z Luo, W Chen, X Shen, G Qin, J Yuan, B Hu, J Lyu, D Pan The British journal of radiology 93 (1105), 20190653, 2020 | 13 | 2020 |
Monte Carlo simulation fused with target distribution modeling via deep reinforcement learning for automatic high-efficiency photon distribution estimation J Ma, Z Piao, S Huang, X Duan, G Qin, L Zhou, Y Xu Photonics Research 9 (3), B45-B56, 2021 | 11 | 2021 |
Using machine learning to unravel the value of radiographic features for the classification of bone tumors D Pan, R Liu, B Zheng, J Yuan, H Zeng, Z He, Z Luo, G Qin, W Chen BioMed research international 2021 (1), 8811056, 2021 | 11 | 2021 |