Predicting FDG-PET Images From Multi-Contrast MRI Using Deep Learning in Patients With Brain Neoplasms.

Journal: Journal of magnetic resonance imaging : JMRI
Published Date:

Abstract

BACKGROUND: F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is valuable for determining presence of viable tumor, but is limited by geographical restrictions, radiation exposure, and high cost.

Authors

  • Jiahong Ouyang
    Stanford University, Stanford CA 94305, USA.
  • Kevin T Chen
    From the Departments of Radiology (K.T.C., F.B.d.C.M., S.S., G.Z.), Electrical Engineering (E.G., J.M.P.), and Neurology and Neurological Sciences (A.B., K.L.P., S.J.S., M.D.G., E.M.), Stanford University, 1201 Welch Rd, Stanford, CA 94305; Department of Engineering Physics, Tsinghua University, Beijing, PR China (J.X.); GE Healthcare, Menlo Park, Calif (M.K.); and Subtle Medical, Menlo Park, CA (E.G.).
  • Rui Duarte Armindo
    Department of Radiology, Stanford University, Stanford, California, USA.
  • Guido Alejandro Davidzon
    Department of Radiology, Stanford University, Stanford, California, USA.
  • Kristina Elizabeth Hawk
    Department of Radiology, Stanford University, Stanford, California, USA.
  • Farshad Moradi
    Department of Radiology, Stanford University, Stanford, California, USA.
  • Jarrett Rosenberg
    Department of Radiology, Stanford University, Stanford, California, USA.
  • Ella Lan
    The Harker School, San Jose, California, USA.
  • Helena Zhang
    Department of Radiology, Stanford University, Stanford, California, USA.
  • Greg Zaharchuk
    Stanford University, Stanford CA 94305, USA.