- 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
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Hwang HJ, Kim H, Seo JB, Ye JC, Oh G, Lee SM, Jang R, Yun J, Kim N, Park HJ, Lee HY, Yoon SH, Shin KE, Lee JW, Kwon W, Sun JS, You S, Chung MH, Gil BM, Lim JK, Lee Y, Hong SJ, Choi YW
- KMID: 2544923
- Korean J Radiol.
- 2023 Aug;24(8):807-820.
- doi: 10.3348/kjr.2023.0088
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... -
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