Radiomics for Lung Cancer Risk Assessment

We aim to increase the efficacy of lung cancer screening with low dose computed tomography (LDCT) by developing methods to accurately predict risk of lung cancer and/or progressive obstructive lung disease at the time of screening.

Animal Models of Human Disease

We have optimized longitudinal medical imaging studies for characterizing novel large animal models of human disease.

Tuning of Mathematical Prediction Models for Lung Cancer

Our web tool allows for exploration and tuning of MPM performance on local patient cohort.

Chest CT Protocols for Radiomic Assessment

Our group has worked on the optimization of CT imaging protocols and/or validation of quantitative CT biomarkers for the assessment of lung structure. 

Radiomics for COPD and Association with Lung Cancer Risk

We are interested in the utilization of CT imaging to explore lung disease etiology and subtypes. 

Impact of the Female Menstrual Cycle on Pulmonary Disease Assessment

The goal of this research is to determine the impact of menstrual cycle related changes in the female lung on imaging biomarkers of pulmonary structure and function assessed by both multi-energy, high spatial resolution CT and hyperpolarized ¹²⁹Xe MRI.