Performance Evaluation of Four Deep Learning-Based CAD Systems and Manual Reading for Pulmonary Nodules Detection, Volume Measurement, and Lung-RADS Classification Under Varying Radiation Doses and Reconstruction Methods

Performance Evaluation of Four Deep Learning-Based CAD Systems and Manual Reading for Pulmonary Nodules Detection, Volume Measurement, and Lung-RADS Classification Under Varying Radiation Doses and Reconstruction Methods

<b>Background:</b> Optimization of pulmonary nodule detection across varied imaging protocols remains challenging. We evaluated four DL-CAD systems and manual reading with volume rendering (VR) for performance under varying radiation doses and reconstruction methods. VR refers to a post-...

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Bibliographic Details
Main Authors: Sifan Chen, Lingqi Gao, Maolu Tan, Ke Zhang, Fajin Lv
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Diagnostics
Subjects:
computer-aided diagnosis
deep learning
volume rendering
pulmonary nodule
phantom study
Online Access:https://www.mdpi.com/2075-4418/15/13/1623
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