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.