Zobrazeno 1 - 10
of 345
pro vyhledávání: '"Yefeng Zheng"'
Autor:
Fenglin Liu, Tingting Zhu, Xian Wu, Bang Yang, Chenyu You, Chenyang Wang, Lei Lu, Zhangdaihong Liu, Yefeng Zheng, Xu Sun, Yang Yang, Lei Clifton, David A. Clifton
Publikováno v:
npj Digital Medicine, Vol 6, Iss 1, Pp 1-15 (2023)
Abstract Deep neural networks have been integrated into the whole clinical decision procedure which can improve the efficiency of diagnosis and alleviate the heavy workload of physicians. Since most neural networks are supervised, their performance h
Externí odkaz:
https://doaj.org/article/8660a4c9237d4be09546ee7d024c40bd
Publikováno v:
Data Science and Engineering, Vol 8, Iss 2, Pp 124-134 (2023)
Abstract We study the problem of multimodal embedding-based entity alignment (EA) between different knowledge graphs. Recent works have attempted to incorporate images (visual context) to address EA in a multimodal view. While the benefits of multimo
Externí odkaz:
https://doaj.org/article/510093c75cc349888d059ab84bcbe647
Autor:
Michela Antonelli, Annika Reinke, Spyridon Bakas, Keyvan Farahani, Annette Kopp-Schneider, Bennett A. Landman, Geert Litjens, Bjoern Menze, Olaf Ronneberger, Ronald M. Summers, Bram van Ginneken, Michel Bilello, Patrick Bilic, Patrick F. Christ, Richard K. G. Do, Marc J. Gollub, Stephan H. Heckers, Henkjan Huisman, William R. Jarnagin, Maureen K. McHugo, Sandy Napel, Jennifer S. Golia Pernicka, Kawal Rhode, Catalina Tobon-Gomez, Eugene Vorontsov, James A. Meakin, Sebastien Ourselin, Manuel Wiesenfarth, Pablo Arbeláez, Byeonguk Bae, Sihong Chen, Laura Daza, Jianjiang Feng, Baochun He, Fabian Isensee, Yuanfeng Ji, Fucang Jia, Ildoo Kim, Klaus Maier-Hein, Dorit Merhof, Akshay Pai, Beomhee Park, Mathias Perslev, Ramin Rezaiifar, Oliver Rippel, Ignacio Sarasua, Wei Shen, Jaemin Son, Christian Wachinger, Liansheng Wang, Yan Wang, Yingda Xia, Daguang Xu, Zhanwei Xu, Yefeng Zheng, Amber L. Simpson, Lena Maier-Hein, M. Jorge Cardoso
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-13 (2022)
International challenges have become the de facto standard for comparative assessment of image analysis algorithms. Here, the authors present the results of a biomedical image segmentation challenge, showing that a method capable of performing well o
Externí odkaz:
https://doaj.org/article/b2b75489b22a48efa4cd6eef2bea9d67
Autor:
Xian Song, Qian Xu, Haiming Li, Qian Fan, Yefeng Zheng, Qiang Zhang, Chunyan Chu, Zhicheng Zhang, Chenglang Yuan, Munan Ning, Cheng Bian, Kai Ma, Yi Qu
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
PurposeUsing deep learning (DL)-based technique, we identify risk factors and create a prediction model for refractory neovascular age-related macular degeneration (nAMD) characterized by persistent disease activity (PDA) in spectral domain optical c
Externí odkaz:
https://doaj.org/article/f40bee382a994c5585a52701d37b0561
Autor:
Shuojia Wang, Weiren Wang, Xiaowen Li, Yafei Liu, Jingming Wei, Jianguang Zheng, Yan Wang, Birong Ye, Ruihui Zhao, Yu Huang, Sixiang Peng, Yefeng Zheng, Yanbing Zeng
Publikováno v:
Frontiers in Aging Neuroscience, Vol 14 (2022)
Objectives: This study firstly aimed to explore predicting cognitive impairment at an early stage using a large population-based longitudinal survey of elderly Chinese people. The second aim was to identify reversible factors which may help slow the
Externí odkaz:
https://doaj.org/article/94d3bf9a42884faf80e8ac39e4881e03
Autor:
Peng Xue, Chao Tang, Qing Li, Yuexiang Li, Yu Shen, Yuqian Zhao, Jiawei Chen, Jianrong Wu, Longyu Li, Wei Wang, Yucong Li, Xiaoli Cui, Shaokai Zhang, Wenhua Zhang, Xun Zhang, Kai Ma, Yefeng Zheng, Tianyi Qian, Man Tat Alexander Ng, Zhihua Liu, Youlin Qiao, Yu Jiang, Fanghui Zhao
Publikováno v:
BMC Medicine, Vol 18, Iss 1, Pp 1-10 (2020)
Abstract Background Colposcopy diagnosis and directed biopsy are the key components in cervical cancer screening programs. However, their performance is limited by the requirement for experienced colposcopists. This study aimed to develop and validat
Externí odkaz:
https://doaj.org/article/c06c6227e5ed47808fa4a272226f3134
Publikováno v:
ACM Computing Surveys; Mar2024, Vol. 56 Issue 3, p1-28, 28p
Autor:
Zeyu Gao, Chang Jia, Yang Li, Xianli Zhang, Bangyang Hong, Jialun Wu, Tieliang Gong, Chunbao Wang, Deyu Meng, Yefeng Zheng, Chen Li
Publikováno v:
IEEE Transactions on Medical Imaging. 41:3611-3623
Tissue segmentation is an essential task in computational pathology. However, relevant datasets for such a pixel-level classification task are hard to obtain due to the difficulty of annotation, bringing obstacles for training a deep learning-based s
Autor:
Zhe Xu, Donghuan Lu, Jie Luo, Yixin Wang, Jiangpeng Yan, Kai Ma, Yefeng Zheng, Raymond Kai-Yu Tong
Publikováno v:
IEEE Transactions on Medical Imaging. 41:3062-3073
Manually segmenting medical images is expertise-demanding, time-consuming and laborious. Acquiring massive high-quality labeled data from experts is often infeasible. Unfortunately, without sufficient high-quality pixel-level labels, the usual data-d
Autor:
Le Zhang, Ryutaro Tanno, Moucheng Xu, Yawen Huang, Kevin Bronik, Chen Jin, Joseph Jacob, Yefeng Zheng, Ling Shao, Olga Ciccarelli, Frederik Barkhof, Daniel C. Alexander
Publikováno v:
Zhang, L, Tanno, R, Xu, M, Huang, Y, Bronik, K, Jin, C, Jacob, J, Zheng, Y, Shao, L, Ciccarelli, O, Barkhof, F & Alexander, D C 2023, ' Learning from multiple annotators for medical image segmentation ', Pattern Recognition, vol. 138, 109400 . https://doi.org/10.1016/j.patcog.2023.109400
Pattern Recognition, 138:109400. Elsevier Limited
Pattern Recognition, 138:109400. Elsevier Limited
Supervised machine learning methods have been widely developed for segmentation tasks in recent years. However, the quality of labels has high impact on the predictive performance of these algorithms. This issue is particularly acute in the medical i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0386380595e7b39715a9cc0fb2d5afff
https://research.vumc.nl/en/publications/6e001fb7-bc86-48c0-bf14-5dde8ed4d297
https://research.vumc.nl/en/publications/6e001fb7-bc86-48c0-bf14-5dde8ed4d297