Developing novel imaging technologies guided by a rigorous understanding of image science.
Explore Our Research Join the LabNovel image acquisition and reconstruction techniques for task-driven imaging and non-circular cone-beam CT orbits for metal artifact reduction.
Detector modeling, material decomposition algorithms, and image-quality modeling for imaging systems with photon-counting and multi-layer detectors.
Algorithms and analysis methods for deep learning reconstruction and post-processing, including approaches that incorporate domain knowledge in learned models.
Methods that use prior knowledge of spatial resolution and noise to remove scanner-dependent variability in radiomics features.
Image chain modeling and model observers for subjective image quality assessment.
Image analysis and quantitative feature extraction, including working-angle prediction for neuro-interventional procedures.
Recognizing distinguished contributions to medical physics.
Abstracts by Huay Din on radiomics feature variance prediction and Yue Fan on focal-spot design optimization both ranked among the top four at the conference.
Limei Ma won first place in the Image-Guided Procedures and Robotic Interventions Early-Career Investigator competition for automatic viewing angle prediction in intracranial aneurysm treatment.