The conventional filtered backprojection (FBP) algorithm employed in reduced dose MDCT acquisitions provides low
reconstruction quality, e.g. high noise level, and many artifacts. Thus, there is the need for efficient reconstruction
methods that have dose reduction potential while providing high reconstruction quality. In this work we present a
comparison study between a statistical iterative reconstruction algorithm called iDose and the FBP algorithm. iDose is a
hybrid iterative reconstruction algorithm which provides enhanced image quality while reducing the radiation dose
compared to conventional algorithms. We report on the performance of the two algorithms with respect to uniformity,
noise characteristics, spatial resolution, and patient studies. With respect to the uniformity of the Hounsfield Units (HU),
we found that the mean HU value remains stable while employing iDose. With iDose the noise is significantly reduced.
This is reflected by an improvement in the contrast-to-noise ratio and in the noise-power-spectrum compared to the FBP.
The measurements of the modulation-transfer-function confirm that with iDose there is no decline in spatial resolution.
In clinical studies, slices reconstructed with the iDose algorithm showed significantly lower mean noise. Inspired by our
phantom and clinical results, we come to the conclusion that iDose is an important tool when considering the reduction
of radiation dose in CT. However, continuous efforts to reduce radiation dose should be further proceeded.