- Digital Radiological Imaging Laboratory (DRIL), led by Dr. Wei Zhao, is working to develop new detector technologies for medical imaging and to investigate their performance in advanced clinical applications. The group investigates imaging performance and design optimization for amorphous selenium flat-panel detectors for digital mammography and digital breast tomosynthesis, as well as advanced detector concepts for improved imaging performance at low dose and high frame rates
- Laboratory for Imaging Research and Informatics (IRIS), led by Dr. Jerome Liang:
Artificial Intelligence (AI) has become as widespread and influential as computers around the world. Although defining AI precisely is challenging, it can be understood as a system’s ability to replicate or simulate human expertise and decision-making. In the Radiology department, we have been focusing on integrating AI into clinical practice, education, and research through the following initiatives:
1. Streamlining image acquisition, interpretation, and storage/retrieval to improve workflow efficiency.
2. Bringing cutting-edge technology and AI knowledge into the classroom to equip the next generation of radiologists with the skills needed to leverage AI in their work.
3. Exploring AI-driven innovations to discover new insights into human biology, enable early detection of abnormalities, and predict future biological developments.
Our department’s AI advancements are showcased in several research projects, such as the development of Computed Tomographic Colonography (CTC) for screening early colorectal cancer, and the enhancement of Low-Dose Computed Tomography (LDCT), which achieved a receiver operating characteristic area Under the Curve (AUC) Score of 0.98 for diagnosing indeterminate pulmonary nodules compared to current gold standard of AUC in the 0.70s. (Click Here for more details)
- Preclinical PET/SPECT/CT Laboratory, led by Dr. Paul Vaska. Our preclinical imaging facility also houses a tri-modality PET/SPECT/CT (Siemens Inveon), a top-tier small-animal imaging platform located in a spacious lab in the main animal facility. All 3 modalities can be accessed in a sequential manner, without removing the animal from the bed, thus providing a high degree of image registration. The PET component features a large field of view (9.9 cm trans-axial x 12.7 cm axial), high spatial resolution (1.5 mm FWHM), and high sensitivity (6.8% coincidence). The CT component provides anatomical information as well as attenuation correction for the PET. It also has fully developed data processing software with all necessary quantitative corrections and multiple image reconstruction options (FBP, OSEM, MAP). The lab includes a new Biodex Atomlab 500 dose calibrator and well counter system, and standard equipment for handling blood samples.
- Stroke, TBI Imaging, and Cancer Imaging Laboratory, led by Dr. Zhao (John) Jiang. This laboratory uses imaging techniques to investigate stroke and TBI pathophysiology and evaluate neuroprotective treatments. Collaborative measures include histology, immunohistochemistry, and behavioral function.
- Wang Neuroimaging Lab, led by: Yicun Wang, PhD., is a tenure-track Assistant Professor of Radiology at Stony Brook University Department of Radiology. His research focuses on Magnetic Resonance Imaging (MRI) physics and the quantitative modeling of MRI signals to identify novel biomarkers in the human brain. Specifically, he develops innovative acquisition and modeling techniques to quantify brain myelination and iron concentration by integrating various MRI metrics, such as T1, T2, T2*, magnetic susceptibility, and magnetization transfer. The overarching goal of his work is to enhance our understanding of MRI-detectable tissue property changes in neuroinflammation and their role in Alzheimer’s disease. Additionally, he develops MRI methods for dynamic imaging of neuro-fluid movement and brain-tissue displacement, as well as advanced modeling approaches to explore their physiological interplay in normal aging and hydrocephalus. The understanding gained from these research efforts is expected to lead to more effective treatments for these debilitating neurological disorders.
