Mitigation of motion-induced artifacts in cone beam computed tomography using deep convolutional neural networks.

Mohammadreza Amirian,Javier A Montoya-Zegarra, Ivo Herzig,Peter Eggenberger Hotz, Lukas Lichtensteiger, Marco Morf,Alexander Züst,Pascal Paysan,Igor Peterlik,Stefan Scheib,Rudolf Marcel Füchslin,Thilo Stadelmann,Frank-Peter Schilling

Medical physics（2023）

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摘要

For the first time, it is demonstrated, also by means of clinical evaluation, that inserting deep neural networks as pre- and post-processing plugins in the existing 3D CBCT reconstruction and trained end-to-end yield significant improvements in image quality and reduction of motion artifacts.

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关键词

cone beam computed tomography,deep learning,motion artifacts

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