Area of research
Radiology, Nuclear Medicine and Imaging · Artificial Intelligence
Research interest
Research interests include Radiomics and Machine Learning in Medical Imaging, MRI in cancer diagnosis, AI in cancer detection, and Advanced MRI Techniques and Applications.
Multi-modal large language models in radiology: principles, applications, and potential
ChatGPT and Other Large Language Models Are Double-edged Swords
Improving breast cancer diagnostics with deep learning for MRI
Differences between human and machine perception in medical diagnosis
Artificial intelligence system reduces false-positive findings in the interpretation of breast ultrasound exams
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization
Magnetic Resonance Imaging in Screening of Breast Cancer
Role of MRI to Assess Response to Neoadjuvant Therapy for Breast Cancer
Abbreviated MR Imaging for Breast Cancer
Deep Neural Networks Improve Radiologists’ Performance in Breast Cancer Screening
Machine learning in breast MRI
Automated Segmentation of Tissues Using CT and MRI: A Systematic Review
Evaluation of a known breast cancer using an abbreviated breast MRI protocol: Correlation of imaging characteristics and pathology with lesion detection and conspicuity
Comparison of conventional DCE‐MRI and a novel golden‐angle radial multicoil compressed sensing method for the evaluation of breast lesion conspicuity
Outcome of small lung nodules missed on hybrid PET/MRI in patients with primary malignancy
Pulmonary Nodules in Patients with Primary Malignancy: Comparison of Hybrid PET/MR and PET/CT Imaging