Jesse Ahlquist, an undergraduate student researcher in our group, presented his work on deep-learning low-dose liver CT imaging at the 30th UC Davis Annual Undergraduate Research, Scholarship & Creative Activities Conference. His study uses convolutional neural networks as a tool to investigate low-dose CT for fat quantification. Jesse’s effort on liver CT is synergistic with our ongoing development of liver parametric PET to enable a multiparametric liver PET/CT technique for imaging of fatty liver disease.