학술지IMA Journal of Applied Mathematics (0272-4960), 89(1), 231 ~ 253
등재유형SCIE
게재일자 20240101
This paper describes the mathematical structure of the ill-posed nonlinear inverse problem of low-dose dental cone-beam computed tomography (CBCT) and explains the advantages of a deep learning-based approach to the reconstruction of computed tomography images over conventional regularization methods.
