The Computational Image Analysis Laboratory, led by Dr. Binsheng Zhao, advances radiology research and practice through the development of state-of-the-art image analysis techniques. We aim to enhance clinical decision-making within personalized precision oncology. Specifically, we innovate and validate novel quantitative imaging biomarkers derived from CT, MRI, and/or PET scans, utilizing radiomics and deep learning (AI) methodologies, to enhance cancer detection, diagnosis, prognosis, and the prediction and evaluation of treatment outcomes.

Through the utilization of our in-house developed image-based response assessment system and a radiomics analysis pipeline, both incorporating proprietary technologies such as solid tumor segmentation and characterization methods, we have established collaborations with researchers worldwide, across academia and industry. For instance, we play a pivotal role as contributors to the Foundation for the National Institutes of Health (FNIH) Biomarkers Consortium – Vol-PACT: Advanced Metrics and Modeling with Volumetric CT for Precision Analysis of Clinical Trial Results.