Effect of Deep Learning Image Reconstruction Algorithms on Radiomic Features of Pulmonary Nodules in Ultra-Low-Dose CT
Zhijuan Zheng,
Yuying Liang,
Zhehao Wu
et al.
Abstract:Objective
The purpose of this study is to explore the impact of deep learning image reconstruction (DLIR) algorithm on the quantification of radiomic features in ultra-low-dose computed tomography (ULD-CT) compared with adaptive statistical iterative reconstruction-Veo (ASIR-V).
Methods
One hundred eighty-three patients with pulmonary nodules underwent standard-dose computed tomography (SDCT) (4.30 ± 0.36 mSv) and ULD-CT (UL-A, 0.57 ± 0.09 mSv or UL-B, … Show more
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