Artifact suppressed dictionary learning for low-dose CT image processing.
作者： Yang Chen , Luyao Shi , Qianjing Feng , Jian Yang , Huazhong Shu
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摘要: Low-dose computed tomography (LDCT) images are often severely degraded by amplified mottle noise and streak artifacts. These artifacts are often hard to suppress without introducing tissue blurring effects. In this paper, we propose to process LDCT images using a novel image-domain algorithm called “artifact suppressed dictionary learning (ASDL).” In this ASDL method, orientation and scale information on artifacts is exploited to train artifact atoms, which are then combined with tissue feature atoms to build three discriminative …
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