Metal Artifact Reduction

4 papers with code • 0 benchmarks • 0 datasets

Metal artifact reduction aims to remove the artifacts introduced by metallic implants in CT images.

Datasets


Greatest papers with code

ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction

liaohaofu/adn 3 Aug 2019

Current deep neural network based approaches to computed tomography (CT) metal artifact reduction (MAR) are supervised methods that rely on synthesized metal artifacts for training.

Computed Tomography (CT) Image-to-Image Translation +2

Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction

liaohaofu/adn 5 Jun 2019

Extensive experiments show that our method significantly outperforms the existing unsupervised models for image-to-image translation problems, and achieves comparable performance to existing supervised models on a synthesized dataset.

Computed Tomography (CT) Image-to-Image Translation +1

Fast Enhanced CT Metal Artifact Reduction using Data Domain Deep Learning

mughanibu/DeepMAR 9 Apr 2019

The subsequent complete projection data is then used with FBP to reconstruct image intended to be free of artifacts.

Computed Tomography (CT) Image Reconstruction +2

DAN-Net: Dual-Domain Adaptive-Scaling Non-local Network for CT Metal Artifact Reduction

zjk1988/DAN-Net 16 Feb 2021

With the rapid development of deep learning in the field of medical imaging, several network models have been proposed for metal artifact reduction (MAR) in CT.

Computed Tomography (CT) Metal Artifact Reduction