翻译(生物学)
计算机科学
图像翻译
图像(数学)
人工智能
领域(数学分析)
编码器
布线(电子设计自动化)
计算机视觉
计算机断层摄影术
迭代重建
嵌入式系统
数学
放射科
化学
数学分析
生物化学
操作系统
信使核糖核酸
基因
医学
作者
Hyun-Jong Kim,Gyutaek Oh,Joon Beom Seo,Hye Jeon Hwang,Sang Min Lee,Jihye Yun,Jong Chul Ye
标识
DOI:10.1088/1361-6560/ac950e
摘要
Abstract Objective. To unify the style of computed tomography (CT) images from multiple sources, we propose a novel multi-domain image translation network to convert CT images from different scan parameters and manufacturers by simply changing a routing vector. Approach. Unlike the existing multi-domain translation techniques, our method is based on a shared encoder and a routable decoder architecture to maximize the expressivity and conditioning power of the network. Main results. Experimental results show that the proposed CT image conversion can minimize the variation of image characteristics caused by imaging parameters, reconstruction algorithms, and hardware designs. Quantitative results and clinical evaluation from radiologists also show that our method can provide accurate translation results. Significance. Quantitative evaluation of CT images from multi-site or longitudinal studies has been a difficult problem due to the image variation depending on CT scan parameters and manufacturers. The proposed method can be utilized to address this for the quantitative analysis of multi-domain CT images.
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