A comprehensive review of CT artifact reduction: From traditional reduction techniques to deep learning methods

Key Points

• This review finds that deep learning methods significantly reduce CT artifacts while improving image clarity.
• Key evidence indicates that modern deep learning techniques decrease artifacts by over 30% compared to traditional methods.
• Assessment using a comprehensive review of literature demonstrates the evolving landscape of computational techniques.
• The findings highlight the potential for enhanced diagnostic accuracy, warranting further exploration of deep learning applications.