Development and Validation of a Deep Learning System for Staging Liver Fibrosis by Using Contrast Agent-enhanced CT Images in the Liver

Choi Kyu Jin; Jang Jong Keon; Lee Seung Soo; Sung Yu Sub; Shim Woo Hyun; Kim Ho Sung; Yun Jessica; Choi Jin-Young; Lee Yedaun; Kang Bo-Kyeong; Kim Jin Hee; Kim So Yeon; Yu Eun Sil

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Development and Validation of a Deep Learning System for Staging Liver Fibrosis by Using Contrast Agent-enhanced CT Images in the Liver

机译：利用造影剂增强CT图像在肝脏中分期肝纤维化深度学习系统的开发与验证

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Purpose: To develop and validate a deep learning system (DLS) for staging liver fibrosis by using CT images in the liver.

机译：目的：通过在肝脏中使用CT图像，开发和验证用于分期肝纤维化的深度学习系统（DLS）。

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《Radiology》 |2018年第3期|共10页
作者
Choi Kyu Jin; Jang Jong Keon; Lee Seung Soo; Sung Yu Sub; Shim Woo Hyun; Kim Ho Sung; Yun Jessica; Choi Jin-Young; Lee Yedaun; Kang Bo-Kyeong; Kim Jin Hee; Kim So Yeon; Yu Eun Sil;
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Hanyang Univ Dept Comp Sci Seoul South Korea;

Univ Ulsan Coll Med Dept Radiol 88 Olymp Ro 43 Gil Seoul 05505 South Korea;

Univ Ulsan Coll Med Dept Radiol 88 Olymp Ro 43 Gil Seoul 05505 South Korea;

Univ Ulsan Coll Med Dept Radiol 88 Olymp Ro 43 Gil Seoul 05505 South Korea;

Univ Ulsan Coll Med Dept Radiol 88 Olymp Ro 43 Gil Seoul 05505 South Korea;

Univ Ulsan Coll Med Dept Radiol 88 Olymp Ro 43 Gil Seoul 05505 South Korea;

Univ Ulsan Coll Med Dept Radiol 88 Olymp Ro 43 Gil Seoul 05505 South Korea;

Yonsei Univ Coll Med Severance Hosp Dept Radiol Seoul South Korea;

Inje Univ Coll Med Haeundae Paik Hosp Dept Radiol Busan South Korea;

Hanyang Univ Sch Med Med Ctr Dept Radiol Seoul South Korea;

Univ Ulsan Coll Med Dept Radiol 88 Olymp Ro 43 Gil Seoul 05505 South Korea;

Univ Ulsan Coll Med Dept Radiol 88 Olymp Ro 43 Gil Seoul 05505 South Korea;

Univ Ulsan Coll Med Dept Diagnost Pathol Asan Med Ctr 88 Olympic-Ro 43-Gil Seoul 05505 South;

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正文语种 eng
中图分类放射医学;
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1. Development and Validation of a Deep Learning System for Staging Liver Fibrosis by Using Contrast Agent-enhanced CT Images in the Liver [J] . Choi Kyu Jin, Jang Jong Keon, Lee Seung Soo, Radiology . 2018,第3期

机译：利用造影剂增强CT图像在肝脏中分期肝纤维化深度学习系统的开发与验证
2. The diagnostic efficacy of quantitative liver MR imaging with diffusion-weighted, SWI, and hepato-specific contrast-enhanced sequences in staging liver fibrosis-a multiparametric approach [J] . Feier Diana, Balassy Csilla, Bastati Nina, European radiology . 2016,第2期

机译：扩散加权，SWI和肝特异性对比增强序列定量肝MR成像对肝纤维化分期的多参数诊断价值
3. Deep learning for staging liver fibrosis on CT: a pilot study [J] . Yasaka Koichiro, Akai Hiroyuki, Kunimatsu Akira, European radiology . 2018,第11期

机译：深入学习肝纤维化CT：试验研究
4. The accurate non-invasive staging of liver fibrosis using deep learning radiomics based on transfer learning of shear wave elastography [C] . Hui Zhou, Kun Wang, Jie Tian Conference on Medical Imaging: Ultrasonic Imaging and Tomography . 2020

机译：基于转移学习的深层学习射频基于剪切波弹性造影的深度学习辐射学准确的非侵入性分期
5. Design and development of a multifunctional nano carrier system for imaging, drug delivery, and cell targeting in cancer research. [D] . Cho, Hoon-Sung. 2010

机译：多功能纳米载体系统的设计和开发，用于癌症研究中的成像，药物输送和细胞靶向。
6. Evaluation of texture features at staging liver fibrosis based on phase contrast X-ray imaging [O] . Jing Wang, Ming Wang, Song Gao, 2018

机译：基于相衬X射线成像评估肝纤维化分期的纹理特征
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Development and Validation of a Deep Learning System for Staging Liver Fibrosis by Using Contrast Agent-enhanced CT Images in the Liver

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