Image quality and dose reduction opportunity of deep learning image reconstruction algorithm for CT: a phantom study.

To assess the impact on image quality and dose reduction of a new deep learning image reconstruction (DLIR) algorithm compared with a hybrid iterative reconstruction (IR) algorithm. Data acquisitions were performed at seven dose levels (CTDI NPS peaks were higher with AV50 than with all DLIR levels and only higher with DLIR-H than with AV100. The average NPS spatial frequencies were higher with DLIR than with IR. For all DLIR levels, TTF New DLIR algorithm reduced noise and improved spatial resolution and detectability without changing the noise texture. Images obtained with DLIR seem to indicate a greater potential for dose optimization than those with hybrid IR. • This study assessed the impact on image quality and radiation dose of a new deep learning image reconstruction (DLIR) algorithm as compared with hybrid iterative reconstruction (IR) algorithm. • The new DLIR algorithm reduced noise and improved spatial resolution and detectability without perceived alteration of the texture, commonly reported with IR. • As compared with IR, DLIR seems to open further possibility of dose optimization.