Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Ruobing Huang"'
Publikováno v:
NeuroImage, Vol 258, Iss , Pp 119341- (2022)
Brain extraction (masking of extra-cerebral tissues) and alignment are fundamental first steps of most neuroimage analysis pipelines. The lack of automated solutions for 3D ultrasound (US) has therefore limited its potential as a neuroimaging modalit
Externí odkaz:
https://doaj.org/article/6eabca83e2504249a1d00a6c84664d90
Autor:
Chaoyu Chen, Xin Yang, Haoran Dou, Ruobing Huang, Xiaoqiong Huang, Xu Wang, Chong Duan, Shengli Li, Wufeng Xue, Pheng Ann Heng, Dong Ni
Publikováno v:
IEEE Access, Vol 8, Pp 173961-173973 (2020)
Deep neural networks are very compelling for medical image segmentation. However, deep models often suffer from notable performance drops in real clinical settings due to the complex appearance shift in daily scannings. Domain adaptation partially ad
Externí odkaz:
https://doaj.org/article/7106b77896ba49b7b261ac2df95224bc
Publikováno v:
Sensors, Vol 14, Iss 1, Pp 1740-1756 (2014)
Implantable devices have important applications in biomedical sensor networks used for biomedical monitoring, diagnosis and treatment, etc. In this paper, an implant intra-body communication (IBC) method based on capacitive coupling has been proposed
Externí odkaz:
https://doaj.org/article/226c21ffbfa344e0bac5afd0679accb1
Autor:
Jian, Wang, Juzheng, Miao, Xin, Yang, Rui, Li, Guangquan, Zhou, Yuhao, Huang, Zehui, Lin, Wufeng, Xue, Xiaohong, Jia, Jianqiao, Zhou, Ruobing, Huang, Dong, Ni
Breast cancer is the most common invasive cancer in women. Besides the primary B-mode ultrasound screening, sonographers have explored the inclusion of Doppler, strain and shear-wave elasticity imaging to advance the diagnosis. However, recognizing u
Externí odkaz:
http://arxiv.org/abs/2008.03435
Autor:
Meizhe Yu, Peili Li, Ruobing Huang, Chunning Xu, Shiyin Zhang, Yanglei Wang, Xuedong Gong, Xiaodong Xing
Publikováno v:
Journal of Materials Chemistry B. 11:734-754
Due to the increasing bacterial resistance to conventional antibiotics, developing safe and effective approaches to combat infections caused by bacteria and biofilms has become an urgent clinical problem. Recently, carbon dots (CDs) have received gre
Autor:
Meizhe Yu, Xiuzhi Guo, Haojie Lu, Peili Li, Ruobing Huang, Chunning Xu, Xuedong Gong, Yuhong Xiao, Xiaodong Xing
Publikováno v:
Carbon. 199:395-406
Autor:
Van T. Manh, Jianqiao Zhou, Xiaohong Jia, Zehui Lin, Wenwen Xu, Zihan Mei, Yijie Dong, Xin Yang, Ruobing Huang, Dong Ni
Ultrasound (US) is the primary imaging technique for the diagnosis of thyroid cancer. However, accurate identification of nodule malignancy is a challenging task that can elude less-experienced clinicians. Recently, many computer-aided diagnosis (CAD
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eeaeaf805d26d800162c83dec236ea42
http://arxiv.org/abs/2207.04219
http://arxiv.org/abs/2207.04219
Autor:
Dong Ni, Xiaoqiong Huang, Shengli Li, Pheng-Ann Heng, Ruobing Huang, Xin Yang, Wufeng Xue, Haoran Dou, Xu Wang, Chaoyu Chen, Chong Duan
Publikováno v:
IEEE Access, Vol 8, Pp 173961-173973 (2020)
Deep neural networks are very compelling for medical image segmentation. However, deep models often suffer from notable performance drops in real clinical settings due to the complex appearance shift in daily scannings. Domain adaptation partially ad
Autor:
Ruobing Huang, Qilong Ying, Zehui Lin, Zijie Zheng, Long Tan, Guoxue Tang, Qi Zhang, Man Luo, Xiuwen Yi, Pan Liu, Weiwei Pan, Jiayi Wu, Baoming Luo, Dong Ni
Publikováno v:
Medical image analysis. 80
Ultrasound (US) plays a vital role in breast cancer screening, especially for women with dense breasts. Common practice requires a sonographer to recognize key diagnostic features of a lesion and record a single or several representative frames durin
Publikováno v:
Resource-Efficient Medical Image Analysis ISBN: 9783031168758
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7969c1852995b977e718fc2415b269fd
https://doi.org/10.1007/978-3-031-16876-5_11
https://doi.org/10.1007/978-3-031-16876-5_11