Our research emphasizes three dimensions: 1) Innovate; 2) Collaborate; 3) Translate. 

Specifically, we pursue interdisciplinary research towards enhanced quantitative image generation and analysis methods for tomographic medical imaging applications (PET, SPECT, optical, acoustic). Our efforts include:

  • Quantitative PET imaging methods for enhanced diagnosis, prognosis and treatment response assessment of cancer patients
  • Radiomics and machine learning methods as applied to PET and SPECT imaging (cancer, cardiovascular disease and Parkinson’s disease)
  • Quantitative SPECT-based dosimetry in radiopharmaceutical therapy (a.k.a. radionuclide or radioligand therapy)
  • Partial volume correction as applied to PET imaging of cancer as well as Alzheimer’s disease
  • Dynamic whole-body PET/CT imaging
  • Statistical tomographic image reconstruction algorithms (including tomosynthesis; e.g. as applied to ultrasound imaging)
  • Optical and photoacoustic imaging through the intact brain for in vivo assessment of brain network activity
  • Cardiac and/or respiratory motion compensation methods (4D/5D imaging)