Our research lies at the intersection of Applied Mathematics and Medical Imaging. We are interested in the following topics:
Mathematical Signal and Image Processing, Medical Imaging, Machine Learning, Deep Learning, Inverse problems, Optimization Algorithms, Parameter Estimation and Robust Control Theory.
Imaging Modalities – PET-CT, PET-MR, SPECT-CT, SPECT-MR, CT, MRI
Specific Topics – Segmentation and Registration, Direct/Indirect Parametric Imaging, Motion estimation/correction, Dual-Biomarker imaging, Absolute Myocardial Perfusion quantification, 3-D/4-D Image Reconstruction, Physiological Segmentation of Dynamic images, Connectivity Analysis/Network Analysis, Resolution Modeling, Task-based assessment, Whole-Body Parametric Imaging, TOF Reconstruction, Partial Volume Correction, Ultra-low dose imaging, Kinetic Modeling, Computational Biology/Physiology (tumor modeling), Radiomics, and Radiogenomics.