Automatic longitudinal mammography analysis for large breast cancer screening cohort
A processing pipeline for longitudinal mammography registration, interpretation, and automatic image labeling using text-based radiology reports to enable efficient and comprehensive imaging data analysis.
Digital twins to patient-specifically optimize breast cancer response to chemotherapy
Image-guided digital twins provide the unique opportunity to systematically evaluate individual breast cancer patient’s response to different chemotherapy dosing-schedule, thereby optimizing the treatment plan.
Patient-specific optimization of nanoparticle convection-enhanced delivery in rGBM
Image-guided model achieved high accuracy for predicting radioactive nanoparticle delivery for rGBM and guided patient-specific placement of delivery catheter(s), so to improving treatment efficacy and reducing side effects.
Image-guided digital twins to predict breast cancer response to neoadjuvant therapy
Integrating MRI data with mechanism-based mathematical modeling successfully predicts breast cancer response to neoadjuvant therapy on a patient-specific basis
Quantitative MRI to characterize tumor microenvironment, vasculature, and blood supply
Novel approaches integrating quantitative MRI analysis and computational fluid dynamics to identify tumor-associated vasculature and to estimate the blood supply and interstitial fluid environment for breast tumors.
in silico MRI validation framework
We developed an in silico validation framework for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) acquisition and analysis methods.