Zobrazeno 1 - 10
of 96
pro vyhledávání: '"Xiangyun Liao"'
Autor:
Linyuan Wang, Xiaofeng Zhang, Congyu Tian, Shu Chen, Yongzhi Deng, Xiangyun Liao, Qiong Wang, Weixin Si
Publikováno v:
Visual Computing for Industry, Biomedicine, and Art, Vol 7, Iss 1, Pp 1-12 (2024)
Abstract Cardiovascular disease, primarily caused by atherosclerotic plaque formation, is a significant health concern. The early detection of these plaques is crucial for targeted therapies and reducing the risk of cardiovascular diseases. This stud
Externí odkaz:
https://doaj.org/article/e6e4d7f687744f868f8e9c0cb3f60f80
Publikováno v:
Computer Assisted Surgery, Vol 29, Iss 1 (2024)
AbstractThe aim of this study is to analyze the risk factors associated with the development of adenomatous and malignant polyps in the gallbladder. Adenomatous polyps of the gallbladder are considered precancerous and have a high likelihood of progr
Externí odkaz:
https://doaj.org/article/7feef945aac948e39e0a8c6976d6f85f
Publikováno v:
BMC Medical Imaging, Vol 23, Iss 1, Pp 1-14 (2023)
Abstract Purpose Segmentation of liver vessels from CT images is indispensable prior to surgical planning and aroused a broad range of interest in the medical image analysis community. Due to the complex structure and low-contrast background, automat
Externí odkaz:
https://doaj.org/article/7421c05112a54aecbe0a428f13dec79d
Autor:
Bin Xu, Xiaofeng Zhang, Congyu Tian, Wei Yan, Yuanqing Wang, Doudou Zhang, Xiangyun Liao, Xiaodong Cai
Publikováno v:
Frontiers in Neurology, Vol 14 (2023)
ObjectiveCerebral white matter hyperintensity can lead to cerebral small vessel disease, MRI images in the brain are used to assess the degree of pathological changes in white matter regions. In this paper, we propose a framework for automatic 3D seg
Externí odkaz:
https://doaj.org/article/f72d5d1e3c1744a39b76b408c3d256b6
Publikováno v:
Mathematics, Vol 11, Iss 23, p 4868 (2023)
Automated segmentation of abdominal organs and tumors in medical images is a challenging yet essential task in medical image analysis. Deep learning has shown excellent performance in many medical image segmentation tasks, but most prior efforts were
Externí odkaz:
https://doaj.org/article/3d57993e2a374db186f8fa53782c6894
Autor:
Xiaofeng Zhang, Yongzhi Deng, Congyu Tian, Shu Chen, Yuanqing Wang, Meng Zhang, Qiong Wang, Xiangyun Liao, Weixin Si
Publikováno v:
Frontiers in Neurology, Vol 14 (2023)
ObjectiveToday, cerebrovascular disease has become an important health hazard. Therefore, it is necessary to perform a more accurate and less time-consuming registration of preoperative three-dimensional (3D) images and intraoperative two-dimensional
Externí odkaz:
https://doaj.org/article/fbbac00d02864cf29251d496e365aa16
Publikováno v:
Remote Sensing, Vol 15, Iss 16, p 3980 (2023)
Feature selection is a typical multiobjective problem including two conflicting objectives. In classification, feature selection aims to improve or maintain classification accuracy while reducing the number of selected features. In practical applicat
Externí odkaz:
https://doaj.org/article/24d470779ce94dcba380118b19c9d78b
Publikováno v:
Computational Visual Media, Vol 5, Iss 4, Pp 363-374 (2020)
Abstract This paper presents a novel mixed reality based navigation system for accurate respiratory liver tumor punctures in radiofrequency ablation (RFA). Our system contains an optical see-through head-mounted display device (OST-HMD), Microsoft Ho
Externí odkaz:
https://doaj.org/article/b51f403d77d2417da2e2f8b4e8d54641
Autor:
Yanjun Peng, Ming Chang, Qiong Wang, Yinling Qian, Yingkui Zhang, Mingqiang Wei, Xiangyun Liao
Publikováno v:
IEEE Access, Vol 8, Pp 30969-30978 (2020)
Unstructured point clouds are a representative shape representation of real-world scenes in 3D vision and graphics. Incompletion inevitably arises, due to the way the set of unorganized points is captured, e.g., as fusion of depth images, merged lase
Externí odkaz:
https://doaj.org/article/c3c6da3160354c509d57d4045c52cc64
Autor:
Junde Xu, Donghao Zhou, Danruo Deng, Jingpeng Li, Cheng Chen, Xiangyun Liao, Guangyong Chen, Pheng Ann Heng
Publikováno v:
Intelligent Computing, Vol 2022 (2022)
Cell images, which have been widely used in biomedical research and drug discovery, contain a great deal of valuable information that encodes how cells respond to external stimuli and intentional perturbations. Meanwhile, to discover rarer phenotypes
Externí odkaz:
https://doaj.org/article/4bfe5a3c9ac14f28b64ef26d441210e8