Image-guided light-induced cancer therapy: in this project, we combine nuclear imaging and 3D optical imaging to locate the tumor with Cu-64-labelled multifunctional nanoparticles and to provide the guidance for infrared laser delivery. The precisely-delivered laser will generate localized heat or toxic chemical species to destruct cancerous cells.
CT reconstruction: advanced algorithms for 3D and 4D reconstruction of limited views, angle and sparse sampling CT data. The degrading factors, such as scatter in CBCT, are also mitigated through measurement- and algorithm-based methods.
SPECT/PET simulation and reconstruction: spatiotemporal 4D reconstruction for cardiac and respiratory SPECT and PET. The attenuation and scatter degradations of image quality are addressed as well.
MRI data analysis and prediction of neurodegenerative disease: both volumetric and functional patterns in the brain, locally or globally, will be used as features in machine learning methods to predict different stages of neurodegenerative disease, such as Alzheimer’s disease.
Deep learning for image completion and enhancement: deep learning methods are development to fill missing data in space physics observations and to enhance CT image quality using reduced radiation dose.