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What is Metal Artefact Reduction in CT Imaging about?

This systematic review evaluates the effectiveness of novel metal artefact reduction (MAR) methods, including machine learning algorithms, in improving image quality of CT scans affected by hip and shoulder implants. The analysis of 36 studies indicates that machine learning methods, particularly Recurrent Neural Network MAR, significantly reduce noise without compromising image quality and are faster than traditional statistical algorithms. The findings suggest that further implementation research is neces

Author

Luciano Elsegood

Language

EN