The use of artificial intelligence in computed tomography image reconstruction - A literature review.
BACKGROUND AND PURPOSE
The use of AI in the process of CT image reconstruction may improve image quality of resultant images and therefore facilitate low-dose CT examinations.


METHODS
Articles in this review were gathered from multiple databases (Google Scholar, Ovid and Monash University Library Database). A total of 17 articles regarding AI use in CT image reconstruction was reviewed, including 1 white paper from GE Healthcare.


RESULTS
DLR algorithms performed better in terms of noise reduction abilities, and image quality preservation at low doses when compared to other reconstruction techniques.


CONCLUSION
Further research is required to discuss clinical application and diagnostic accuracy of DLR algorithms, but AI is a promising dose-reduction technique with future computational advances.
['Zhang|Ziyu|Z|', 'Seeram|Euclid|E|']
D001185:Artificial Intelligence D006801:Humans D011857:Radiographic Image Interpretation, Computer-Assisted D014057:Tomography, X-Ray Computed
Convolutional neural networks Deep learning Dose reduction Generative adversarial networks Machine learning