Faculty Spotlight: Tom Huber

Tom Huber (Physics) co-authored a presentation and proceedings paper, “Simulating scanner- and algorithm-specific 3D CT noise texture using physics-informed 2D and 2.5D generative neural network models” at the Society of Photo-Optical Instrumentation Engineers conference on Medical Imaging in February. The goal of this project is to develop AI Deep Learning models to better understand the sources of image noise in medical CT scans. The six other co-authors are researchers at the Mayo Clinic in Rochester.