Current Research and Scholarly Interests
AI in Medicine
Biomedical Physics
Multimodal Imaging
Medical Device
Biomedical Optics
Photoacoustic/Thermoacoustic Imaging
Optical Imaging (Microscopy, OCT, DOT, FMT)
Ultrasound Imaging
1. Artificial intelligence (AI) has great potential for improving the efficiency, precision, accuracy, and overall quality of radiation therapy for cancer patients. AI platforms are still not widely adopted in clinical practice due to challenges associated with the clinical development and implementation of AI-based tools in radiation oncology. The goal of this project is to address these challenges with innovative concepts and strategic developments.
2. A multimodal imaging platform that combines the strengths of several different imaging modalities has the capability to characterize biological tissue more completely, offering improved diagnosis, management, and treatment of diseases. While multimodality images can be obtained by performing each individual modality separately without integrating them into a single platform, it is, however, time-consuming to acquire multimodality images through such a process. Additionally, it is hard to avoid errors from the required complex image registration, and more importantly, impossible to capture dynamic biological processes simultaneously. This project has demonstrated a multimodal imaging system integrating three emerging biomedical imaging techniques: photoacoustic imaging (PAI), optical coherence tomography (OCT), and ultrasound imaging (USI) to obtain optical absorption, scattering, and acoustic properties of tissue simultaneously. Several applications of the multimodal imaging platform have been explored preclinically.
3. X-ray luminescence computed tomography (XLCT) has been recently proposed as a new imaging modality by detecting the luminescent emission signals arising from the interaction between X-ray and the media. Compared to the clinically widely used X-ray CT (anatomical imaging), XLCT represents significant progress in X-ray-based imaging techniques, as X-ray-based molecular or functional imaging becomes achievable in XLCT. Moreover, compared to conventional pure optic-based molecular or functional imaging, XLCT offers two main advantages. First, autofluorescence, problematic for fluorescence imaging, can be avoided. Second, deep tissue in vivo imaging with high optical contrast and spatial resolution becomes achievable. However, progress in this area is significantly hindered by technological challenges posed by the fact that currently most XLCT systems take a long time to acquire whole-body images (low speed). Additionally, XLCT has been entirely reliant on conventional nanophosphors emitting light in the visible or near-infrared spectrum region (700-1000 nm) with high photon absorption and scattering in biological tissues, limiting XLCT for deeper tissue imaging (insufficient imaging penetration depth) and reducing spatial resolution (limited spatial resolution). This project has been focused on addressing these challenges with innovative concepts and strategic developments.
