Zobrazeno 1 - 10
of 730
pro vyhledávání: '"Liu, ZaiYi"'
Autor:
Tang, Fenghe, Xu, Ronghao, Yao, Qingsong, Fu, Xueming, Quan, Quan, Zhu, Heqin, Liu, Zaiyi, Zhou, S. Kevin
The generative self-supervised learning strategy exhibits remarkable learning representational capabilities. However, there is limited attention to end-to-end pre-training methods based on a hybrid architecture of CNN and Transformer, which can learn
Externí odkaz:
http://arxiv.org/abs/2408.05815
Autor:
Zhou, Lei, Zhang, Yuzhong, Zhang, Jiadong, Qian, Xuejun, Gong, Chen, Sun, Kun, Ding, Zhongxiang, Wang, Xing, Li, Zhenhui, Liu, Zaiyi, Shen, Dinggang
Publikováno v:
2024,IEEE Transactions on Medical Imaging
Automated breast tumor segmentation on the basis of dynamic contrast-enhancement magnetic resonance imaging (DCE-MRI) has shown great promise in clinical practice, particularly for identifying the presence of breast disease. However, accurate segment
Externí odkaz:
http://arxiv.org/abs/2408.05803
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:
Lin, Jiatai, Han, Guoqiang, Xu, Xuemiao, Liang, Changhong, Wong, Tien-Tsin, Chen, C. L. Philip, Liu, Zaiyi, Han, Chu
Class activation mapping~(CAM), a visualization technique for interpreting deep learning models, is now commonly used for weakly supervised semantic segmentation~(WSSS) and object localization~(WSOL). It is the weighted aggregation of the feature map
Externí odkaz:
http://arxiv.org/abs/2309.03509
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:
Ma, Wenao, Chen, Cheng, Abrigo, Jill, Mak, Calvin Hoi-Kwan, Gong, Yuqi, Chan, Nga Yan, Han, Chu, Liu, Zaiyi, Dou, Qi
Intracerebral hemorrhage (ICH) is the second most common and deadliest form of stroke. Despite medical advances, predicting treat ment outcomes for ICH remains a challenge. This paper proposes a novel prognostic model that utilizes both imaging and t
Externí odkaz:
http://arxiv.org/abs/2307.12858
Autor:
Zhang, Jianpeng, Ye, Xianghua, Zhang, Jianfeng, Tang, Yuxing, Xu, Minfeng, Guo, Jianfei, Chen, Xin, Liu, Zaiyi, Zhou, Jingren, Lu, Le, Zhang, Ling
Lung cancer is a leading cause of death worldwide and early screening is critical for improving survival outcomes. In clinical practice, the contextual structure of nodules and the accumulated experience of radiologists are the two core elements rela
Externí odkaz:
http://arxiv.org/abs/2307.10824
Autor:
Wang, Hao, Lin, Jiatai, Li, Danyi, Wang, Jing, Zhao, Bingchao, Shi, Zhenwei, Pan, Xipeng, Wang, Huadeng, Li, Bingbing, Liang, Changhong, Han, Guoqiang, Liang, Li, Han, Chu, Liu, Zaiyi
Mitosis detection is one of the fundamental tasks in computational pathology, which is extremely challenging due to the heterogeneity of mitotic cell. Most of the current studies solve the heterogeneity in the technical aspect by increasing the model
Externí odkaz:
http://arxiv.org/abs/2307.05889
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
One-shot medical landmark detection gains much attention and achieves great success for its label-efficient training process. However, existing one-shot learning methods are highly specialized in a single domain and suffer domain preference heavily i
Externí odkaz:
http://arxiv.org/abs/2306.07615