Deep learning reconstruction improves computer-aided pulmonary nodule detection and measurement accuracy for ultra-low-dose chest CT

Deep learning reconstruction improves computer-aided pulmonary nodule detection and measurement accuracy for ultra-low-dose chest CT

Abstract Purpose To compare the image quality and pulmonary nodule detectability and measurement accuracy between deep learning reconstruction (DLR) and hybrid iterative reconstruction (HIR) of chest ultra-low-dose CT (ULDCT). Materials and Methods Participants who underwent chest standard-dose CT (...

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Bibliographic Details
Main Authors: Jinhua Wang, Zhenchen Zhu, Zhengsong Pan, Weixiong Tan, Wei Han, Zhen Zhou, Ge Hu, Zhuangfei Ma, Yinghao Xu, Zhoumeng Ying, Xin Sui, Zhengyu Jin, Lan Song, Wei Song
Format: Article
Language:English
Published: BMC 2025-05-01
Series:BMC Medical Imaging
Subjects:
Lung nodules
Tomography, X-ray computed
Deep learning reconstruction
Image quality
Online Access:https://doi.org/10.1186/s12880-025-01746-6
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