Hye Jeon Hwang, Hyunjong Kim, Joon Beom Seo, Jong Chul Ye, Gyutaek Oh, Sang Min Lee, Ryoungwoo Jang, Jihye Yun, Namkug Kim, Hee Jun Park, Ho Yun Lee, Soon Ho Yoon, Kyung Eun Shin, Jae Wook Lee, Woocheol Kwon, Joo Sung Sun, Seulgi You, Myung Hee Chung, Bo Mi Gil, Jae-Kwang Lim, Youkyung Lee, Su Jin Hong, Yo Won Choi
OBJECTIVE: To assess whether computed tomography (CT) conversion across different scan parameters and manufacturers using a routable generative adversarial network (RouteGAN) can improve the accuracy and variability in quantifying interstitial lung disease (ILD) using a deep learning-based automated software. MATERIALS AND METHODS: This study included patients with ILD who underwent thin-section CT. Unmatched CT images obtained using scanners from four manufacturers (vendors A-D), standard- or low-radiation doses, and sharp or medium kernels were classified into groups 1-7 according to acquisition conditions...
August 2023: Korean Journal of Radiology: Official Journal of the Korean Radiological Society