End-to-End Deep Learning CT Image Reconstruction for Metal Artifact Reduction

Metal artifacts are common in CT-guided interventions due to the presence of metallic instruments. These artifacts often obscure clinically relevant structures, which can complicate the intervention. In this work, we present a deep learning CT reconstruction called iCTU-Net for the reduction of meta...

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Bibliographic Details

Published in:	Applied Sciences
Main Authors:	Dominik F. Bauer, Constantin Ulrich, Tom Russ, Alena-Kathrin Golla, Lothar R. Schad, Frank G. Zöllner
Format:	Article
Language:	English
Published:	MDPI AG 2021-12-01
Subjects:	image reconstruction deep learning metal artifacts computed tomography
Online Access:	https://www.mdpi.com/2076-3417/12/1/404