Generative Adversarial Network-Based Image Conversion Among Different Computed Tomography Protocols and Vendors: Effects on Accuracy and Variability in Quantifying Regional Disease Patterns of Interstitial Lung Disease

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.
Korean Journal of Radiology ; : 807-820, 2023.
Artículo en Inglés | WPRIM | ID: wpr-1002395

Documentos relacionados

  1. Generative Adversarial Network-Based Image Conversion Among Different Computed Tomography Protocols and Vendors: Effects on Accuracy and Variability in Quantifying Regional Disease Patterns of Interstitial Lung Disease.