Comparative evaluation of deep learning-based and conventional reconstruction techniques for image quality enhancement in low-dose chest computed tomography.

Fiche publication

Date publication

mai 2025

Journal

Journal of thoracic disease

Auteurs

Membres identifiés du Cancéropôle Est :
Pr LOFFROY Romaric

Tous les auteurs :
Zhang Z, Liu C, Zhou S, Yang X, Loffroy R, Kim HW, Shan L

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/40529728

Résumé

With the increasing use of computed tomography (CT) in clinical practice, greater attention is being paid to the radiation dose. There are numerous methods available for reducing the CT radiation dose, but enhancement via a reconstruction algorithm is the most effective method. This study aimed to evaluate the performance of a proposed deep learning (DL) algorithm for low-dose chest CT image reconstruction among patients with pulmonary diseases and to compare it with several mainstream iterative reconstruction (IR) techniques.