Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Bingzhong Jing"'
Autor:
Xueyi Zheng, Bingzhong Jing, Zihan Zhao, Ruixuan Wang, Xinke Zhang, Haohua Chen, Shuyang Wu, Yan Sun, Jiangyu Zhang, Hongmei Wu, Dan Huang, Wenbiao Zhu, Jianning Chen, Qinghua Cao, Hong Zeng, Jinling Duan, Yuanliang Luo, Zhicheng Li, Wuhao Lin, Runcong Nie, Yishu Deng, Jingping Yun, Chaofeng Li, Dan Xie, Muyan Cai
Publikováno v:
iScience, Vol 27, Iss 3, Pp 109243- (2024)
Summary: Accurate tumor diagnosis by pathologists relies on identifying specific morphological characteristics. However, summarizing these unique morphological features in tumor classifications can be challenging. Although deep learning models have b
Externí odkaz:
https://doaj.org/article/98bab18ed8654461bee553d5ab97b2df
Autor:
Qingqing Cai, Chaofeng LI, Liang Wang, Chuanmiao Xie, Yuchen Zhang, Yishu Deng, Qihua Zou, Bingzhong Jing, Peiqiang Cai, Xiaopeng Tian, Yi Cao, Yu Yang, Bingzong LI, Fang Liu, Zhihua LI, Zaiyi Liu, Shiting Feng, Tingsheng Peng, Yujun Dong, Xinyan Wang, Guangying Ruan, Yun He, Huiqiang Huang, Yang Liang
Publikováno v:
HemaSphere, Vol 7, p e68913b0 (2023)
Externí odkaz:
https://doaj.org/article/9ed4ff4f15bd4edb987694b3b169cda9
Publikováno v:
Life, Vol 13, Iss 3, p 743 (2023)
Background: Delineating the lesion area is an important task in image-based diagnosis. Pixel-wise classification is a popular approach to segmenting the region of interest. However, at fuzzy boundaries, such methods usually result in glitches, discon
Externí odkaz:
https://doaj.org/article/3c67e15f291041cfad5325da0c86b01f
Autor:
Xi Chen, Xun Cao, Bingzhong Jing, Weixiong Xia, Liangru Ke, Yanqun Xiang, Kuiyuan Liu, Mengyun Qiang, Chixiong Liang, Jianpeng Li, Mingyong Gao, Wangzhong Li, Jingjing Miao, Guoying Liu, Zhuochen Cai, Shuhui Lv, Xiang Guo, Chaofeng Li, Xing Lv
Publikováno v:
Frontiers in Oncology, Vol 10 (2020)
We aimed to develop a nomogram integrating MRI-based tumor burden features (MTBF), nodal necrosis, and some clinical factors to forecast the distant metastasis-free survival (DMFS) of patients suffering from non-metastatic nasopharyngeal carcinoma (N
Externí odkaz:
https://doaj.org/article/6c9e6988f4b545e3b24426bebd9a2ee0
Autor:
Chaofeng Li, Bingzhong Jing, Liangru Ke, Bin Li, Weixiong Xia, Caisheng He, Chaonan Qian, Chong Zhao, Haiqiang Mai, Mingyuan Chen, Kajia Cao, Haoyuan Mo, Ling Guo, Qiuyan Chen, Linquan Tang, Wenze Qiu, Yahui Yu, Hu Liang, Xinjun Huang, Guoying Liu, Wangzhong Li, Lin Wang, Rui Sun, Xiong Zou, Shanshan Guo, Peiyu Huang, Donghua Luo, Fang Qiu, Yishan Wu, Yijun Hua, Kuiyuan Liu, Shuhui Lv, Jingjing Miao, Yanqun Xiang, Ying Sun, Xiang Guo, Xing Lv
Publikováno v:
Cancer Communications, Vol 38, Iss 1, Pp 1-11 (2018)
Abstract Background Due to the occult anatomic location of the nasopharynx and frequent presence of adenoid hyperplasia, the positive rate for malignancy identification during biopsy is low, thus leading to delayed or missed diagnosis for nasopharyng
Externí odkaz:
https://doaj.org/article/a20c695534d745e589e845c3dbcbbb75
Autor:
Yishu Deng, Dan Hou, Bin Li, Xing Lv, Liangru Ke, Mengyun Qiang, Taihe Li, Bingzhong Jing, Chaofeng Li
Publikováno v:
Journal of Medical and Biological Engineering. 42:604-612
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4cbe2767d585227939dda61e322e5f27
https://doi.org/10.1007/s40846-022-00710-x
https://doi.org/10.1007/s40846-022-00710-x
Autor:
Xing Lv, Ying-Ying Huang, Yishu Deng, Yang Liu, Wenze Qiu, Meng-yun Qiang, Wei-Xiong Xia, Bingzhong Jing, Chen-Yang Feng, Haohua Chen, Xun Cao, Jia-Yu Zhou, Hao-yang Huang, Ze-Jiang Zhan, Ying Deng, Lin-Quan Tang, Hai-Qiang Mai, Ying Sun, Chuanmiao Xie, Xiang Guo, Liang-Ru Ke, Chaofeng Li
Precise detection of recurrence in patients with treated nasopharyngeal carcinoma (NPC) facilitates timely intervention and prolongs survival. However, there is no compelling tool realizing real-time precise recurrence detection as scale hitherto. He
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b4d5781811ed0192a52477c6aef6bf7e
https://doi.org/10.21203/rs.3.rs-2705522/v1
https://doi.org/10.21203/rs.3.rs-2705522/v1
Autor:
Bin Li, Shao bin Lin, Huiyan Luo, Chu ming Yuan, Jun Huang, Hai xin Chen, Bin Chen, Qin ming Chen, Sharvesh Raj Seeruttun, Feng Zhou, Zi-Xian Wang, Chaofeng Li, Wencheng Tan, Linna Luo, Heng Ying Pu, Guo Liang Xu, Longjun He, Yun He, Ying Jin, Caisheng He, Bingzhong Jing, Yishu Deng, Rui-Hua Xu, Qiubao Wu, De wang Huang, Yin Li
Publikováno v:
The Lancet Oncology. 20:1645-1654
Summary Background Upper gastrointestinal cancers (including oesophageal cancer and gastric cancer) are the most common cancers worldwide. Artificial intelligence platforms using deep learning algorithms have made remarkable progress in medical imagi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::09591aaac90429be3c2638c4eb20c295
https://doi.org/10.1016/s1470-2045(19)30637-0
https://doi.org/10.1016/s1470-2045(19)30637-0
Autor:
Bin Li, Wei-Xiong Xia, Xiang Guo, Bingzhong Jing, Yishu Deng, Chuanmiao Xie, Lujun Shen, Liangru Ke, Chaofeng Li, Xing Lv, Ying Sun
Publikováno v:
SSRN Electronic Journal.
Background: No consensus in sequence selection for artificial intelligence model development has been achieved, we aimed to explore whether contrast-enhanced magnetic resonance imaging (ceMRI) could be substituted in the identification and segmentati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c6564e80d63f651f42ec034a8700b84f
https://doi.org/10.2139/ssrn.3868836
https://doi.org/10.2139/ssrn.3868836
Autor:
Yishu, Deng, Chaofeng, Li, Xing, Lv, Weixiong, Xia, Lujun, Shen, Bingzhong, Jing, Bin, Li, Xiang, Guo, Ying, Sun, Chuanmiao, Xie, Liangru, Ke
Publikováno v:
Computer Methods and Programs in Biomedicine. 217:106702
Administration of contrast is not desirable for all cases in clinical setting, and no consensus in sequence selection for deep learning model development has been achieved, thus we aim to explore whether contrast-enhanced magnetic resonance imaging (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::44c9381a5c58708a1b72a46f617134ac
https://doi.org/10.1016/j.cmpb.2022.106702
https://doi.org/10.1016/j.cmpb.2022.106702