Zobrazeno 1 - 10
of 1 104
pro vyhledávání: '"Lu, Le"'
Autor:
Qiu, Zhongwei, Chao, Hanqing, Liu, Wenbin, Shen, Yixuan, Lu, Le, Yan, Ke, Jin, Dakai, Bian, Yun, Jiang, Hui
Survival analysis using pathology images poses a considerable challenge, as it requires the localization of relevant information from the multitude of tiles within whole slide images (WSIs). Current methods typically resort to a two-stage approach, w
Externí odkaz:
http://arxiv.org/abs/2409.03804
Autor:
Chen, Wei, Huang, Zhen, Xie, Liang, Lin, Binbin, Li, Houqiang, Lu, Le, Tian, Xinmei, Cai, Deng, Zhang, Yonggang, Wan, Wenxiao, Shen, Xu, Ye, Jieping
Large Language Models (LLMs) tend to prioritize adherence to user prompts over providing veracious responses, leading to the sycophancy issue. When challenged by users, LLMs tend to admit mistakes and provide inaccurate responses even if they initial
Externí odkaz:
http://arxiv.org/abs/2409.01658
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
Cross-Phase Mutual Learning Framework for Pulmonary Embolism Identification on Non-Contrast CT Scans
Autor:
Bai, Bizhe, Zhou, Yan-Jie, Hu, Yujian, Mok, Tony C. W., Xiang, Yilang, Lu, Le, Zhang, Hongkun, Xu, Minfeng
Pulmonary embolism (PE) is a life-threatening condition where rapid and accurate diagnosis is imperative yet difficult due to predominantly atypical symptomatology. Computed tomography pulmonary angiography (CTPA) is acknowledged as the gold standard
Externí odkaz:
http://arxiv.org/abs/2407.11529
Autor:
Hu, Yujian, Xiang, Yilang, Zhou, Yan-Jie, He, Yangyan, Yang, Shifeng, Du, Xiaolong, Den, Chunlan, Xu, Youyao, Wang, Gaofeng, Ding, Zhengyao, Huang, Jingyong, Zhao, Wenjun, Wu, Xuejun, Li, Donglin, Zhu, Qianqian, Li, Zhenjiang, Qiu, Chenyang, Wu, Ziheng, He, Yunjun, Tian, Chen, Qiu, Yihui, Lin, Zuodong, Zhang, Xiaolong, He, Yuan, Yuan, Zhenpeng, Zhou, Xiaoxiang, Fan, Rong, Chen, Ruihan, Guo, Wenchao, Zhang, Jianpeng, Mok, Tony C. W., Li, Zi, Lu, Le, Lang, Dehai, Li, Xiaoqiang, Wang, Guofu, Lu, Wei, Huang, Zhengxing, Xu, Minfeng, Zhang, Hongkun
Chest pain symptoms are highly prevalent in emergency departments (EDs), where acute aortic syndrome (AAS) is a catastrophic cardiovascular emergency with a high fatality rate, especially when timely and accurate treatment is not administered. Howeve
Externí odkaz:
http://arxiv.org/abs/2406.15222
Autor:
Guo, Guangyu, Yao, Jiawen, Xia, Yingda, Mok, Tony C. W., Zheng, Zhilin, Han, Junwei, Lu, Le, Zhang, Dingwen, Zhou, Jian, Zhang, Ling
The absence of adequately sufficient expert-level tumor annotations hinders the effectiveness of supervised learning based opportunistic cancer screening on medical imaging. Clinical reports (that are rich in descriptive textual details) can offer a
Externí odkaz:
http://arxiv.org/abs/2405.14230
Medical Vision-Language Pretraining (Med-VLP) establishes a connection between visual content from medical images and the relevant textual descriptions. Existing Med-VLP methods primarily focus on 2D images depicting a single body part, notably chest
Externí odkaz:
http://arxiv.org/abs/2404.15272
Autor:
Cao, Weiwei, Zhang, Jianpeng, Xia, Yingda, Mok, Tony C. W., Li, Zi, Ye, Xianghua, Lu, Le, Zheng, Jian, Tang, Yuxing, Zhang, Ling
Radiologists highly desire fully automated versatile AI for medical imaging interpretation. However, the lack of extensively annotated large-scale multi-disease datasets has hindered the achievement of this goal. In this paper, we explore the feasibi
Externí odkaz:
http://arxiv.org/abs/2404.04936
Autor:
Fang, Wei, Tang, Yuxing, Guo, Heng, Yuan, Mingze, Mok, Tony C. W., Yan, Ke, Yao, Jiawen, Chen, Xin, Liu, Zaiyi, Lu, Le, Zhang, Ling, Xu, Minfeng
In the realm of medical 3D data, such as CT and MRI images, prevalent anisotropic resolution is characterized by high intra-slice but diminished inter-slice resolution. The lowered resolution between adjacent slices poses challenges, hindering optima
Externí odkaz:
http://arxiv.org/abs/2404.04878