Low-contrast detectability and potential for radiation dose reduction using deep learning image reconstruction-A 20-reader study on a semi-anthropomorphic liver phantom.

ABSTRACT:

Background

A novel deep learning image reconstruction (DLIR) algorithm for CT has recently been clinically approved.

Purpose

To assess low-contrast detectability and dose reduction potential for CT images reconstructed with the DLIR algorithm and compare with filtered back projection (FBP) and hybrid iterative reconstruction (IR).

Material and methods

A customized upper-abdomen phantom containing four cylindrical liver inserts with low-contrast lesions was scanned at CT dose indexes of 5, 10, 15, 20 and 25 mGy. Images were reconstructed with FBP, 50% hybrid IR (IR50), and DLIR of low strength (DLL), medium strength (DLM) and high strength (DLH). Detectability was assessed by 20 independent readers using a two-alternative forced choice approach. Dose reduction potentia

SUBMITTER: Njolstad T 

PROVIDER: S-EPMC8980706 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature