Lung CT harmonization of paired reconstruction kernel images using generative adversarial networks.

ABSTRACT:

Background

The kernel used in CT image reconstruction is an important factor that determines the texture of the CT image. Consistency of reconstruction kernel choice is important for quantitative CT-based assessment as kernel differences can lead to substantial shifts in measurements unrelated to underlying anatomical structures.

Purpose

In this study, we investigate kernel harmonization in a multi-vendor low-dose CT lung cancer screening cohort and evaluate our approach's validity in quantitative CT-based assessments.

Methods

Using the National Lung Screening Trial, we identified CT scan pairs of the same sessions with one reconstructed from a soft tissue kernel and one from a hard kernel. In total, 1000 pairs of five different paired kernel types (200 each) were ide

SUBMITTER: Krishnan AR 

PROVIDER: S-EPMC11321937 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature