Zobrazeno 1 - 10
of 73
pro vyhledávání: '"Yuan, Mingze"'
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
Autor:
Yuan, Mingze, Bao, Peng, Yuan, Jiajia, Shen, Yunhao, Chen, Zifan, Xie, Yi, Zhao, Jie, Chen, Yang, Zhang, Li, Shen, Lin, Dong, Bin
With the rapid development of artificial intelligence, large language models (LLMs) have shown promising capabilities in mimicking human-level language comprehension and reasoning. This has sparked significant interest in applying LLMs to enhance var
Externí odkaz:
http://arxiv.org/abs/2311.01918
Autor:
Dong, Hexin, Yao, Jiawen, Tang, Yuxing, Yuan, Mingze, Xia, Yingda, Zhou, Jian, Lu, Hong, Zhou, Jingren, Dong, Bin, Lu, Le, Zhang, Li, Liu, Zaiyi, Shi, Yu, Zhang, Ling
Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer in which the tumor-vascular involvement greatly affects the resectability and, thus, overall survival of patients. However, current prognostic prediction methods fail to explicitly and
Externí odkaz:
http://arxiv.org/abs/2308.00507
Autor:
Yuan, Mingze, Xia, Yingda, Chen, Xin, Yao, Jiawen, Wang, Junli, Qiu, Mingyan, Dong, Hexin, Zhou, Jingren, Dong, Bin, Lu, Le, Zhang, Li, Liu, Zaiyi, Zhang, Ling
Gastric cancer is the third leading cause of cancer-related mortality worldwide, but no guideline-recommended screening test exists. Existing methods can be invasive, expensive, and lack sensitivity to identify early-stage gastric cancer. In this stu
Externí odkaz:
http://arxiv.org/abs/2307.04525
Though achieving excellent performance in some cases, current unsupervised learning methods for single image denoising usually have constraints in applications. In this paper, we propose a new approach which is more general and applicable to complica
Externí odkaz:
http://arxiv.org/abs/2304.08384
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:
Dong, Hexin, Chen, Zifan, Yuan, Mingze, Xie, Yutong, Zhao, Jie, Yu, Fei, Dong, Bin, Zhang, Li
As one of the most challenging and practical segmentation tasks, open-world semantic segmentation requires the model to segment the anomaly regions in the images and incrementally learn to segment out-of-distribution (OOD) objects, especially under a
Externí odkaz:
http://arxiv.org/abs/2205.08083
Autor:
Yuan, Mingze, Richardt, Christian
Publikováno v:
BMVC 2021
Omnidirectional 360{\deg} images have found many promising and exciting applications in computer vision, robotics and other fields, thanks to their increasing affordability, portability and their 360{\deg} field of view. The most common format for st
Externí odkaz:
http://arxiv.org/abs/2112.14331
360{\deg} cameras can capture complete environments in a single shot, which makes 360{\deg} imagery alluring in many computer vision tasks. However, monocular depth estimation remains a challenge for 360{\deg} data, particularly for high resolutions
Externí odkaz:
http://arxiv.org/abs/2111.15669