A New Algorithm for Automatically Calculating Noise, Spatial Resolution, and Contrast Image Quality Metrics: Proof-of-Concept and Agreement With Subjective Scores in Phantom and Clinical Abdominal CT.

Objectives: The aims of this study were to develop a proof-of-concept computer algorithm to automatically determine noise, spatial resolution, and contrast-related image quality (IQ) metrics in abdominal portal venous phase computed tomography (CT) imaging and to assess agreement between resulting objective IQ metrics and subjective radiologist IQ ratings.

Materials And Methods: An algorithm was developed to calculate noise, spatial resolution, and contrast IQ parameters. The algorithm was subsequently used on 2 datasets of anthropomorphic phantom CT scans, acquired on 2 different scanners (n = 57 each), and on 1 dataset of patient abdominal CT scans (n = 510).

Finding the optimal tube current and iterative reconstruction strength in liver imaging; two needles in one haystack.

Objectives: The aim of the study was to find the lowest possible tube current and the optimal iterative reconstruction (IR) strength in abdominal imaging.

Material And Methods: Reconstruction software was used to insert noise, simulating the use of a lower tube current. A semi-anthropomorphic abdominal phantom (Quality Assurance in Radiology and Medicine, QSA-543, Moehrendorf, Germany) was used to validate the performance of the ReconCT software (S1 Appendix).