Iterative Image Reconstruction Algorithms for CT Metal Artifact Reduction: A Review

2013 ◽  
Vol 3 (2) ◽  
pp. 111-117
Author(s):  
Jing Wang
2019 ◽  
Vol 23 (03) ◽  
pp. e68-e81 ◽  
Author(s):  
Iman Khodarahmi ◽  
Amanda Isaac ◽  
Elliot K. Fishman ◽  
Danoob Dalili ◽  
Jan Fritz

AbstractPromising outcomes of hip replacement interventions in this era of aging populations have led to higher demands for hip arthroplasty procedures. These require effective methods and techniques for the detection of postoperative outcomes and complications. Based on the presence or absence of radiographic findings, magnetic resonance imaging (MRI) and computed tomography (CT) may be required to detect and further characterize different causes of failing implants. Yet metal-related artifacts degrade image quality and pose significant challenges for adequate image quality. To mitigate such artifacts in MRI, a set of techniques, collectively known as metal artifact reduction sequence (MARS) MRI, were developed that optimize the framework of the conventional pulse sequences and exploit novel multispectral and multispatial imaging methods such as Slice Encoding for Metal Artifact Correction (SEMAC) and Multi-Acquisition Variable-Resonance Image Combination (MAVRIC). Metal-induced artifacts on CT can be effectively reduced with virtual monochromatic reconstruction of dual-energy CT data sets, metal artifact reduction reconstruction algorithms, and postprocessing image visualization techniques.


2018 ◽  
Vol 226 ◽  
pp. 04048
Author(s):  
Nikolay V. Gapon ◽  
Evgenii A. Semenishchev ◽  
Oxana S. Balabaeva ◽  
Arina A. Skorikova ◽  
Olga A. Tokareva ◽  
...  

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.


Sign in / Sign up

Export Citation Format

Share Document