Rigid and non-rigid motion artifact reduction in X-ray CT using attention module

•Existing methods are limited to specific motions or customized CT systems.•We propose a new real-time method using residual learning and an attention module.•Our model is a generalized framework to handle any CT setups and motion types. [Display omitted] Motion artifacts are a major factor that can...

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Veröffentlicht in:	Medical image analysis 2021-01, Vol.67, p.101883-101883, Article 101883
Hauptverfasser:	Ko, Youngjun, Moon, Seunghyuk, Baek, Jongduk, Shim, Hyunjung
Format:	Artikel
Sprache:	eng
Schlagworte:	Attention module Benchmarks Computed tomography CT motion artifact reduction Datasets Deep learning Dental materials Medical imaging Modules Noise reduction Perceptual loss Real time Residual block
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