Rate My Professor Xiu Wang

Her research specializations include medical image computing and analysis, deep learning, radiomics, and machine learning for biomedical applications such as tumor segmentation, cancer prognosis, PET/CT imaging, brain MR image registration, epileptic seizure detection, and lesion segmentation in multiple sclerosis and Alzheimer's disease. Key publications are "Multi-task deep learning for medical image computing and analysis: A review" (Computers in Biology and Medicine, 2022), "A Likelihood and Local Constraint Level Set Model for Liver Tumor Segmentation from CT Volumes" (IEEE Transactions on Bio-Medical Engineering, 2013), "18F-FDG PET/CT radiomic predictors of pathologic complete response (pCR) to neoadjuvant chemotherapy in breast cancer patients" (European Journal of Nuclear Medicine and Molecular Imaging, 2020), "Epileptic seizure detection with EEG textural features and imbalanced classification based on EasyEnsemble learning" (International Journal of Neural Systems, 2019), "SwitchNet: Adaptive Distribution Switching in UNet for Brain Lesion Segmentation" (2026), and "Forecasting individualized progression of Alzheimer’s disease using structural MRI and population spatiotemporal priors" (2026). With 174 publications and over 2,454 citations, her contributions advance AI-driven diagnostics in biomedical imaging.