Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Ronghua, Yan"'
Autor:
Jiangyu Guo, Shuang Liang, Huahui Liu, Liping Luo, Shanshan Wu, Sainan Guan, Ying Liu, Yongyan He, Erjiao Xu, Ronghua Yan
Publikováno v:
International Journal of Hyperthermia, Vol 41, Iss 1 (2024)
Purpose To explore the feasibility and safety of a microwave ablation (MWA) strategy involving intraductal chilled saline perfusion (ICSP) via percutaneous transhepatic cholangial drainage (PTCD) combined with ultrasound-magnetic resonance (US-MR) fu
Externí odkaz:
https://doaj.org/article/119da475b263480b8e1a9805e5b2929a
Autor:
Sainan Guan, Ronghua Yan, Xiaomin Chen, Weiqiang Chen, Xi Zhou, Minghui Zhou, Zhengneng Xie, Wen Tan, Yongyan He, Juan Fu, Fan Yuan, Erjiao Xu
Publikováno v:
Frontiers in Oncology, Vol 13 (2023)
ObjectiveThis study aimed to retrospectively investigate the use of oral contrast-enhanced ultrasonography (O-CEUS) in assessing the thickness of the gastric wall for gastric cancer (GC) screening and to establish screening strategies for GC with dif
Externí odkaz:
https://doaj.org/article/4987d39728b3421d9e9201ee23790765
Publikováno v:
Frontiers in Endocrinology, Vol 14 (2023)
ObjectivesTo construct a prognostic nomogram to predict the ablation zone disappearance for patients with papillary thyroid microcarcinoma (PTMC) after microwave ablation (MWA).Materials and methodsFrom April 2020 to April 2022, patients with PTMC wh
Externí odkaz:
https://doaj.org/article/9dedb624a8954658be2c720f9f0793f9
Autor:
Yujia You, Yinglin Long, Ronghua Yan, Liping Luo, Man Zhang, Lu Li, Qingjing Zeng, Kai Li, Rongqin Zheng, Erjiao Xu
Publikováno v:
Frontiers in Oncology, Vol 11 (2021)
AimTo explore whether ablation safety could be improved by ultrasound (US)-magnetic resonance (MR) fusion imaging for hepatocellular carcinoma (HCC) proximal to the hilar bile ducts (HBDs) through a preliminary comparative study.MethodsBetween Januar
Externí odkaz:
https://doaj.org/article/7c4ec4c380d845af98b256e7f2fbae67
Publikováno v:
Journal of Hepatocellular Carcinoma. 10:631-642
Liping Luo,1,2,* Ronghua Yan,3,4,* Qingjing Zeng,2 Yinglin Long,2 Xuqi He,2 Kai Li,2 Erjiao Xu1 1Department of Medical Ultrasonics, The Eighth Affiliated Hospital of Sun Yat-sen University, Shenzhen, Peopleâs Republic of China; 2Departme
Autor:
Yinglin Long, Ronghua Yan, Kai Li, Liping Luo, Qingjing Zeng, Lei Tan, Man Zhang, Rongqin Zheng, Erjiao Xu
Publikováno v:
International Journal of Hyperthermia, Vol 36, Iss 1, Pp 139-144 (2019)
Purpose: The purpose of this study was to investigate the feasibility, safety and efficacy of intra-procedural contrast-enhanced ultrasound (CEUS) monitoring of the radiofrequency ablation (RFA) of liver cancers adjacent to gallbladder (GB) without G
Externí odkaz:
https://doaj.org/article/c29fc367cbf045df8e0dc0aba6e619a9
Autor:
Liping Luo, Ronghua Yan, Qingjing Zeng, Kai Li, Rongqin Zheng, Lei Tan, Erjiao Xu, Yinglin Long, Man Zhang
Publikováno v:
International Journal of Hyperthermia, Vol 36, Iss 1, Pp 139-144 (2019)
Purpose: The purpose of this study was to investigate the feasibility, safety and efficacy of intra-procedural contrast-enhanced ultrasound (CEUS) monitoring of the radiofrequency ablation (RFA) of liver cancers adjacent to gallbladder (GB) without G
Publikováno v:
Journal of the Indian Society of Remote Sensing. 47:91-100
Feature extraction is a preprocessing step for hyperspectral image classification. Principal component analysis only uses the spectral information, but it does not use spatial information of a hyperspectral image. Both spatial and spectral informatio
Autor:
Yu Zhang, Zhi Zeng, Qingjian Ye, Ronghua Yan, Juan Cheng, Mengxiong Li, Jia Wang, Changyan Liang, Mixuan Yi
Publikováno v:
Oncotarget
// Juan Cheng 1, * , Zhi Zeng 3, * , Qingjian Ye 1, * , Yu Zhang 1 , Ronghua Yan 2 , Changyan Liang 1 , Jia Wang 1 , Mengxiong Li 1, * , Mixuan Yi 4 1 Department of Gynecology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630
Publikováno v:
2017 International Conference on the Frontiers and Advances in Data Science (FADS).
Both spatial and spectral information is used when a hyperspectral image is modeled as a tensor. However, this model does not consider both the class and within-class information about the spectral features of ground objects. This means that further