A multi-stage deep learning framework for half-detector truncation and metal artifact reduction in CBCT
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Background: Cone-beam computed tomography (CBCT) is widely utilized for its high spatial resolution and compact design. However, image quality is often compromised in the half-detector (HD) geometry, where data truncation arising... ...
