https://www.selleckchem.com/products/AC-220.html
To evaluate the performance of a Deep Learning Image Reconstruction (DLIR) algorithm in pediatric head CT for improving image quality and lesion detection with 0.625mm thin-slice images. Low-dose axial head CT scans of 50 children with 120kV, 0.8s rotation and age-dependent 150-220mA tube current were selected. Images were reconstructed at 5mm and 0.625mm slice thickness using Filtered back projection (FBP), Adaptive statistical iterative reconstruction-v at 50% strength (50%ASIR-V) (as reference standard), 100%ASIR-V and DLIR-high (DL-H
Like
Comment
Share
