Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Liying Qu"'
Autor:
Weisong Zhao, Xiaoshuai Huang, Jianyu Yang, Liying Qu, Guohua Qiu, Yue Zhao, Xinwei Wang, Deer Su, Xumin Ding, Heng Mao, Yaming Jiu, Ying Hu, Jiubin Tan, Shiqun Zhao, Leiting Pan, Liangyi Chen, Haoyu Li
Publikováno v:
Light: Science & Applications, Vol 12, Iss 1, Pp 1-19 (2023)
Abstract In fluorescence microscopy, computational algorithms have been developed to suppress noise, enhance contrast, and even enable super-resolution (SR). However, the local quality of the images may vary on multiple scales, and these differences
Externí odkaz:
https://doaj.org/article/7e232bd85b52466fa3fd76a7522dd77a
Autor:
Peng Zhang, Yunyun Duan, Guocan Gu, Liying Qu, Dan Xiao, Tianshu Xi, Changcun Pan, Ya’ou Liu, Liwei Zhang
Publikováno v:
Frontiers in Oncology, Vol 13 (2023)
ObjectiveDiffuse intrinsic pontine gliomas (DIPGs) are rare but devastating diseases. This retrospective cross-sectional study aimed to investigate the clinical, radiological, and pathological features of DIPGs.Materials and methodsThe clinical data
Externí odkaz:
https://doaj.org/article/b621918696424c10a8d72777f1961dc4
Autor:
Peng Zhang, Guocan Gu, Yunyun Duan, Zhizheng Zhuo, Changcun Pan, Pengcheng Zuo, Yi Wang, Xiaoou Li, Zhuang Jiang, Liying Qu, Yaou Liu, Liwei Zhang
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
BackgroundPrevious studies have identified alterations in structural connectivity of patients with glioma. However, white matter (WM) integrity measured by diffusion kurtosis imaging (DKI) in pediatric patients with brainstem glioma (BSG) was lack of
Externí odkaz:
https://doaj.org/article/f1c3756b196047b2957b4a40787d2ad5
Autor:
Wan Liu, Qi Lu, Zhizheng Zhuo, Yuxing Li, Yunyun Duan, Pinnan Yu, Liying Qu, Chuyang Ye, Yaou Liu
Publikováno v:
NeuroImage, Vol 250, Iss , Pp 118934- (2022)
Convolutional neural networks have achieved state-of-the-art performance for white matter (WM) tract segmentation based on diffusion magnetic resonance imaging (dMRI). However, the segmentation can still be difficult for challenging WM tracts with th
Externí odkaz:
https://doaj.org/article/83b8389b9b6842dc90abdd8532c77dde
Autor:
Junjie Li, Yong Zhi Wang, Jinyuan Weng, Liying Qu, Minghao Wu, Min Guo, Jun Sun, Geli Hu, Xiaodong Gong, Xing Liu, Yunyun Duan, Zhizheng Zhuo, Wenqing Jia, Yaou Liu
Publikováno v:
American Journal of Neuroradiology; Dec2023, Vol. 44 Issue 12, p1464-1470, 7p
Autor:
Junjie Li, Peng Zhang, Liying Qu, Ting Sun, Yunyun Duan, Minghao Wu, Jinyuan Weng, Zhaohui Li, Xiaodong Gong, Xing Liu, Yongzhi Wang, Wenqing Jia, Xiaorui Su, Qiang Yue, Jianrui Li, Zhiqiang Zhang, Frederik Barkhof, Raymond Y. Huang, Ken Chang, Haris Sair, Chuyang Ye, Liwei Zhang, Zhizheng Zhuo, Yaou Liu
Publikováno v:
Journal of Magnetic Resonance Imaging. John Wiley and Sons Inc.
Li, J, Zhang, P, Qu, L, Sun, T, Duan, Y, Wu, M, Weng, J, Li, Z, Gong, X, Liu, X, Wang, Y, Jia, W, Su, X, Yue, Q, Li, J, Zhang, Z, Barkhof, F, Huang, R Y, Chang, K, Sair, H, Ye, C, Zhang, L, Zhuo, Z & Liu, Y 2023, ' Deep Learning for Noninvasive Assessment of H3 K27M Mutation Status in Diffuse Midline Gliomas Using MR Imaging ', Journal of Magnetic Resonance Imaging . https://doi.org/10.1002/jmri.28606
Li, J, Zhang, P, Qu, L, Sun, T, Duan, Y, Wu, M, Weng, J, Li, Z, Gong, X, Liu, X, Wang, Y, Jia, W, Su, X, Yue, Q, Li, J, Zhang, Z, Barkhof, F, Huang, R Y, Chang, K, Sair, H, Ye, C, Zhang, L, Zhuo, Z & Liu, Y 2023, ' Deep Learning for Noninvasive Assessment of H3 K27M Mutation Status in Diffuse Midline Gliomas Using MR Imaging ', Journal of Magnetic Resonance Imaging . https://doi.org/10.1002/jmri.28606
Background: Determination of H3 K27M mutation in diffuse midline glioma (DMG) is key for prognostic assessment and stratifying patient subgroups for clinical trials. MRI can noninvasively depict morphological and metabolic characteristics of H3 K27M
Autor:
Ting Sun, Yongzhi Wang, Xing Liu, Zhaohui Li, Jie Zhang, Jing Lu, Liying Qu, Sven Haller, Yunyun Duan, Zhizheng Zhuo, Dan Cheng, Xiaolu Xu, Wenqing Jia, Yaou Liu
Publikováno v:
Neuro-Oncology.
BackgroundPrognostic models for spinal cord astrocytoma patients are lacking due to the low incidence of the disease. Here, we aim to develop a fully automated deep learning (DL) pipeline for stratified overall survival (OS) prediction based on preop
Autor:
Weisong Zhao, Xiaoshuai Huang, Jianyu Yang, Guohua Qiu, Liying Qu, Yue Zhao, Shiqun Zhao, Ziying Luo, Xinwei Wang, Yaming Jiu, Heng Mao, Xumin Ding, Jiubin Tan, Ying Hu, Leiting Pan, Liangyi Chen, Haoyu Li
In fluorescence microscopy, computational algorithms have been developed to suppress noise, enhance contrast, and even enable super-resolution (SR). However, the local quality of the images may vary on multiple scales, and these differences can lead
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4994e994c6052d0fe49c9ee8a0c2e8dd
https://doi.org/10.1101/2022.12.01.518675
https://doi.org/10.1101/2022.12.01.518675
Autor:
Zhizheng Zhuo, Jie Zhang, Yunyun Duan, Liying Qu, Chenlu Feng, Xufang Huang, Dan Cheng, Xiaolu Xu, Ting Sun, Zhaohui Li, Xiaopeng Guo, Xiaodong Gong, Yongzhi Wang, Wenqing Jia, Decai Tian, Xinghu Zhang, Fudong Shi, Sven Haller, Frederik Barkhof, Chuyang Ye, Yaou Liu
Publikováno v:
Zhuo, Z, Zhang, J, Duan, Y, Qu, L, Feng, C, Huang, X, Cheng, D, Xu, X, Sun, T, Li, Z, Guo, X, Gong, X, Wang, Y, Jia, W, Tian, D, Zhan, X, Shi, F, Haller, S, Barkhof, F, Ye, C & Liu, Y 2022, ' Automated Classification of Intramedullary Spinal Cord Tumors and Inflammatory Demyelinating Lesions Using Deep Learning ', Radiology. Artificial intelligence, vol. 4, no. 6, e210292 . https://doi.org/10.1148/ryai.210292
Radiol Artif Intell
Radiology. Artificial intelligence, 4(6):e210292. Radiological Society of North America Inc.
Radiol Artif Intell
Radiology. Artificial intelligence, 4(6):e210292. Radiological Society of North America Inc.
Accurate differentiation of intramedullary spinal cord tumors and inflammatory demyelinating lesions and their subtypes are warranted because of their overlapping characteristics at MRI but with different treatments and prognosis. The authors aimed t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::973b6adbd87b56bee5e36ea5da4bf26b
https://research.vumc.nl/en/publications/301a5cfa-218b-4647-a6c0-02259626b35e
https://research.vumc.nl/en/publications/301a5cfa-218b-4647-a6c0-02259626b35e
Autor:
Liangyi Chen, Weisong Zhao, Xiaoshuai Huang, Guohua Qiu, Jianyu Yang, Liying Qu, Zhenqian Han, Xiangyu Li, Yue Zhao, Shiqun Zhao, Liuju Li, Ziying Luo, Xinwei Wang, Guanyu Shang, Huijie Hao, Yaming Jiu, Heng Mao, XUMIN Ding, Jiubin Tan, Jian Liu, Ying Hu, Leiting Pan, Haoyu Li
In fluorescence microscopy, computational algorithms have been developed to suppress noise, enhance contrast, and even enable super-resolution (SR). The local quality of the images may vary on multiple scales and these differences can lead to misconc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::617e4c19a6e6454528bec74548540751
https://doi.org/10.21203/rs.3.rs-2222345/v1
https://doi.org/10.21203/rs.3.rs-2222345/v1