Zobrazeno 1 - 10
of 478
pro vyhledávání: '"YIN Xiaoli"'
Autor:
XU Xiaojun, YE Minjie, WANG Yuchen, WANG Wenxia, QIAN Sheng, YE Dandi, PAN Lele, HU Xin, YIN Xiaoli, LI Meihua, LING Guangyao
Publikováno v:
Shanghai Jiaotong Daxue xuebao. Yixue ban, Vol 43, Iss 5, Pp 606-610 (2023)
Objective·To explore the characteristics of sensory gating and its variation in children with first episode schizophrenia (COS) by using a new technique of prepulse suppression (PI).Methods·By using the ERP recording and analysis system of brain pr
Externí odkaz:
https://doaj.org/article/32a2ee7025f445ab9b707c3ded3a79ef
Autor:
Huang, Wei, Liu, Wei, Zhang, Xiaoming, Yin, Xiaoli, Han, Xu, Li, Chunli, Gao, Yuan, Shi, Yu, Lu, Le, Zhang, Ling, Zhang, Lei, Yan, Ke
The early detection and precise diagnosis of liver tumors are tasks of critical clinical value, yet they pose significant challenges due to the high heterogeneity and variability of liver tumors. In this work, a precise LIver tumor DIAgnosis network
Externí odkaz:
http://arxiv.org/abs/2407.13217
Esophageal varices (EV), a serious health concern resulting from portal hypertension, are traditionally diagnosed through invasive endoscopic procedures. Despite non-contrast computed tomography (NC-CT) imaging being a less expensive and non-invasive
Externí odkaz:
http://arxiv.org/abs/2407.13210
Autor:
Mok, Tony C. W., Li, Zi, Bai, Yunhao, Zhang, Jianpeng, Liu, Wei, Zhou, Yan-Jie, Yan, Ke, Jin, Dakai, Shi, Yu, Yin, Xiaoli, Lu, Le, Zhang, Ling
Establishing dense anatomical correspondence across distinct imaging modalities is a foundational yet challenging procedure for numerous medical image analysis studies and image-guided radiotherapy. Existing multi-modality image registration algorith
Externí odkaz:
http://arxiv.org/abs/2402.18933
Autor:
Bai, Fan, Yan, Ke, Bai, Xiaoyu, Mao, Xinyu, Yin, Xiaoli, Zhou, Jingren, Shi, Yu, Lu, Le, Meng, Max Q. -H.
Medical image analysis using deep learning is often challenged by limited labeled data and high annotation costs. Fine-tuning the entire network in label-limited scenarios can lead to overfitting and suboptimal performance. Recently, prompt tuning ha
Externí odkaz:
http://arxiv.org/abs/2308.04911
Autor:
Yan, Ke, Yin, Xiaoli, Xia, Yingda, Wang, Fakai, Wang, Shu, Gao, Yuan, Yao, Jiawen, Li, Chunli, Bai, Xiaoyu, Zhou, Jingren, Zhang, Ling, Lu, Le, Shi, Yu
Liver tumor segmentation and classification are important tasks in computer aided diagnosis. We aim to address three problems: liver tumor screening and preliminary diagnosis in non-contrast computed tomography (CT), and differential diagnosis in dyn
Externí odkaz:
http://arxiv.org/abs/2307.08268
Autor:
Yuan, Mingze, Xia, Yingda, Dong, Hexin, Chen, Zifan, Yao, Jiawen, Qiu, Mingyan, Yan, Ke, Yin, Xiaoli, Shi, Yu, Chen, Xin, Liu, Zaiyi, Dong, Bin, Zhou, Jingren, Lu, Le, Zhang, Ling, Zhang, Li
Real-world medical image segmentation has tremendous long-tailed complexity of objects, among which tail conditions correlate with relatively rare diseases and are clinically significant. A trustworthy medical AI algorithm should demonstrate its effe
Externí odkaz:
http://arxiv.org/abs/2304.00212
Autor:
Chen, Jieneng, Xia, Yingda, Yao, Jiawen, Yan, Ke, Zhang, Jianpeng, Lu, Le, Wang, Fakai, Zhou, Bo, Qiu, Mingyan, Yu, Qihang, Yuan, Mingze, Fang, Wei, Tang, Yuxing, Xu, Minfeng, Zhou, Jian, Zhao, Yuqian, Wang, Qifeng, Ye, Xianghua, Yin, Xiaoli, Shi, Yu, Chen, Xin, Zhou, Jingren, Yuille, Alan, Liu, Zaiyi, Zhang, Ling
Human readers or radiologists routinely perform full-body multi-organ multi-disease detection and diagnosis in clinical practice, while most medical AI systems are built to focus on single organs with a narrow list of a few diseases. This might sever
Externí odkaz:
http://arxiv.org/abs/2301.12291
Autor:
Yu, Zhide, Yin, Xiaoli, Lu, Baoyue, Zhang, Linan, Ma, Yonghao, Chen, Yiman, Feng, Yuwei, Han, Chong, Shu, Hu
Publikováno v:
In Aquaculture Reports December 2024 39
Autor:
Lu, Baoyue, Zhang, Linan, Yu, Zhide, Yang, Jinlin, Xue, Xiaowen, Feng, Yuwei, Chen, Yiman, Han, Chong, Liu, Ruiqi, Yin, Xiaoli, Shu, Hu
Publikováno v:
In Aquaculture Reports December 2024 39