条件生成对抗网络从单管电压 CT 扫描仪生成伪低单能量 CT 图像。

Conditional generative adversarial networks to generate pseudo low monoenergetic CT image from a single-tube voltage CT scanner.

机构信息

Department of Medical Radiation Sciences, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan.

Department of Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan.

出版信息

Phys Med. 2021 Mar;83:46-51. doi: 10.1016/j.ejmp.2021.02.015. Epub 2021 Mar 8.

DOI:10.1016/j.ejmp.2021.02.015

PMID:33706150

Abstract

PURPOSE

To generate pseudo low monoenergetic CT images of the abdomen from 120-kVp CT images with cGAN.

MATERIALS AND METHODS

We retrospectively included 48 patients who underwent contrast-enhanced abdominal CT using dual-energy CT. We reconstructed paired data sets of 120 kVp CT images and virtual low monoenergetic (55-keV) CT images. cGAN was prepared to generate pseudo 55-keV CT images from 120-kVp CT images. The pseudo 55 keV CT images in epoch 10, 50, 100, and 500 were compared to the 55 keV images generated using peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM).

RESULTS

The PSNRs were 28.0, 28.5, 28.6, and 28.8 at epochs 10, 50, 100, and 500, respectively. The SSIM was approximately constant from epochs 50 to 500.

CONCLUSION

Pseudo low monoenergetic abdominal CT images were generated from 120-kVp CT images using cGAN, and the images had good quality similar to that of monochromatic images obtained with DECT software.

摘要

目的

利用条件生成对抗网络（cGAN）从 120kVp CT 图像生成腹部伪低单能量 CT 图像。

材料与方法

我们回顾性地纳入了 48 例使用双能 CT 进行腹部增强 CT 检查的患者。我们重建了 120kVp CT 图像和虚拟低单能量（55keV）CT 图像的配对数据集。cGAN 用于从 120kVp CT 图像生成伪 55keV CT 图像。比较了第 10、50、100 和 500 个时步生成的伪 55keV CT 图像与使用峰值信噪比（PSNR）和结构相似性指数（SSIM）生成的 55keV 图像。