Purpose To evaluate the effect of different numbers of basis images and the use of metal artifact reduction (MAR) on the production and reduction of artifacts in cone-beam computed tomography images. Materials and Methods An acrylic resin phantom with a metal alloy sample was scanned, with 450 or 720 basis images and with or without MAR. Standard deviation values for the test areas (around th...

Recently, both supervised and unsupervised deep learning methods have been widely applied on the CT metal artifact reduction (MAR) task. Supervised such as Dual Domain Network (Du-DoNet) work well simulation data; however, their performance clinical data is limited due to domain gap. Unsupervised are more generalized, but do not eliminate artifacts completely through sole processing image domai...

The standardized OASIS Security Assertion Markup Language (SAML) has become one of the most deployed frameworks in federated identity management even though it focuses only on single sign-on. Answering industry’s pursuit of the reduction of user-management costs and enabling cost-efficient deployment because of its browser-based profiles, SAML is believed to become widely used soon. With the re...