Metal artifact reduction for small metal implants on CT: Which image reconstruction algorithm performs better?

2020 ◽  
Vol 127 ◽  
pp. 108970 ◽  
Author(s):  
Aurélie Grandmougin ◽  
Omar Bakour ◽  
Nicolas Villani ◽  
Cedric Baumann ◽  
Hélène Rousseau ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Reconstruction Algorithm ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Image Reconstruction Algorithm ◽  
Metal Implants

Metal artifact reduction image reconstruction algorithm for CT of implanted metal orthopedic devices: a work in progress

2009 ◽  
Vol 38 (8) ◽  
pp. 797-802 ◽  
Author(s):  
Patrick T. Liu ◽  
William P. Pavlicek ◽  
Mary B. Peter ◽  
Mark J. Spangehl ◽  
Catherine C. Roberts ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Reconstruction Algorithm ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Image Reconstruction Algorithm ◽  
Work In Progress

Single-Energy Retrospective Metal Artifact Reduction Using Adaptive Thresholding for Metal Implants in the Abdomen and Pelvis

2020 ◽  
Vol 44 (3) ◽  
pp. 443-449
Author(s):  
Sujithraj Dommaraju ◽  
Masoud Nakhaei ◽  
Da Zhang ◽  
Andres Camacho ◽  
Johannes Boos ◽  
...  
Keyword(s):  
Adaptive Thresholding ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Metal Implants

scholarly journals CT Image Reconstruction Algorithm to Reduce Metal Artifact

2006 ◽  
Vol 72 (724) ◽  
pp. 1888-1894
Author(s):  
Michihiko KOSEKI ◽  
Shuhei HASHIMOTO ◽  
Shinpei SATO ◽  
Hitoshi KIMURA ◽  
Norio INOU
Keyword(s):  
Image Reconstruction ◽  
Reconstruction Algorithm ◽  
Metal Artifact ◽  
Ct Image ◽  
Image Reconstruction Algorithm ◽  
Ct Image Reconstruction

scholarly journals Metal artifact reduction on MRI images

2018 ◽  
Vol 226 ◽  
pp. 04048
Author(s):  
Nikolay V. Gapon ◽  
Evgenii A. Semenishchev ◽  
Oxana S. Balabaeva ◽  
Arina A. Skorikova ◽  
Olga A. Tokareva ◽  
...  
Keyword(s):  
Neural Network ◽  
Image Reconstruction ◽  
State Of The Art ◽  
Geometric Model ◽  
Similarity Criterion ◽  
Experimental Results ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Trained Neural Network

This article examines the method of image reconstruction, which aims to restore the exposed areas on MRI images. The algorithm is based on a geometric model for patch synthesis. The lost pixels are recovered by copying pixel values from the source using a similarity criterion. We used a trained neural network to choose the “best similar” patch. Experimental results show that the proposed method outperforms widely used state-of-the-art methods.

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