Shengdong Nie
University of Shanghai for Science and Technology(CN)
Publications by Year
Research Areas
Radiomics and Machine Learning in Medical Imaging, Lung Cancer Diagnosis and Treatment, Medical Image Segmentation Techniques, Advanced MRI Techniques and Applications, AI in cancer detection
Most-Cited Works
- → A deep residual learning network for predicting lung adenocarcinoma manifesting as ground-glass nodule on CT images(2019)108 cited
- → Rapid Assessment of Deep Frying Oil Quality as Well as Water and Fat Contents in French Fries by Low-Field Nuclear Magnetic Resonance(2019)78 cited
- → Classification of Parkinson's disease based on multi-modal features and stacking ensemble learning(2020)76 cited
- → The Abnormality of Topological Asymmetry between Hemispheric Brain White Matter Networks in Alzheimer’s Disease and Mild Cognitive Impairment(2017)75 cited
- → Dynamic thalamus parcellation from resting‐state fMRI data(2015)66 cited
- → Image Segmentation Based on Level Set Method(2012)64 cited
- → Segmentation of pulmonary nodules in CT images based on 3D‐UNET combined with three‐dimensional conditional random field optimization(2020)61 cited
- → Computer-aided diagnosis of ground-glass opacity pulmonary nodules using radiomic features analysis(2019)58 cited
- → Rapid identification of edible oil species using supervised support vector machine based on low-field nuclear magnetic resonance relaxation features(2018)54 cited
- → The inversion of 2D NMR relaxometry data using L1 regularization(2016)53 cited