Zobrazeno 1 - 10
of 205
pro vyhledávání: '"Zhou, Xinrui"'
Autor:
Zhou, Xinrui, Huang, Yuhao, Dou, Haoran, Chen, Shijing, Chang, Ao, Liu, Jia, Long, Weiran, Zheng, Jian, Xu, Erjiao, Ren, Jie, Huang, Ruobing, Cheng, Jun, Xue, Wufeng, Ni, Dong
In the medical field, the limited availability of large-scale datasets and labor-intensive annotation processes hinder the performance of deep models. Diffusion-based generative augmentation approaches present a promising solution to this issue, havi
Externí odkaz:
http://arxiv.org/abs/2409.17091
Echocardiography (ECHO) video is widely used for cardiac examination. In clinical, this procedure heavily relies on operator experience, which needs years of training and maybe the assistance of deep learning-based systems for enhanced accuracy and e
Externí odkaz:
http://arxiv.org/abs/2406.14098
Autor:
Wang, Hongsheng, Zhang, Lizao, Zhong, Zhangnan, Xu, Shuolin, Zhou, Xinrui, Zhang, Shengyu, Xu, Huahao, Wu, Fei, Lin, Feng
Reconstructing 3D human bodies from realistic motion sequences remains a challenge due to pervasive and complex occlusions. Current methods struggle to capture the dynamics of occluded body parts, leading to model penetration and distorted motion. Re
Externí odkaz:
http://arxiv.org/abs/2405.12724
In the animation industry, 3D modelers typically rely on front and back non-overlapped concept designs to guide the 3D modeling of anime characters. However, there is currently a lack of automated approaches for generating anime characters directly f
Externí odkaz:
http://arxiv.org/abs/2405.12505
Autor:
Wang, Hongsheng, Zhang, Weiyue, Liu, Sihao, Zhou, Xinrui, Li, Jing, Tang, Zhanyun, Zhang, Shengyu, Wu, Fei, Lin, Feng
Although 3D Gaussian Splatting (3DGS) has recently made progress in 3D human reconstruction, it primarily relies on 2D pixel-level supervision, overlooking the geometric complexity and topological relationships of different body parts. To address thi
Externí odkaz:
http://arxiv.org/abs/2405.12477
Autor:
Chang, Ao, Tao, Xing, Yang, Xin, Huang, Yuhao, Zhou, Xinrui, Zeng, Jiajun, Huang, Ruobing, Ni, Dong
Interactive medical image segmentation refers to the accurate segmentation of the target of interest through interaction (e.g., click) between the user and the image. It has been widely studied in recent years as it is less dependent on abundant anno
Externí odkaz:
http://arxiv.org/abs/2308.13746
Autor:
Zhou, Han, Ni, Dong, Chang, Ao, Zhou, Xinrui, Chen, Rusi, Chen, Yanlin, Liu, Lian, Liang, Jiamin, Huang, Yuhao, Han, Tong, Liu, Zhe, Fan, Deng-Ping, Yang, Xin
Ultrasound (US) imaging is indispensable in clinical practice. To diagnose certain diseases, sonographers must observe corresponding dynamic anatomic structures to gather comprehensive information. However, the limited availability of specific US vid
Externí odkaz:
http://arxiv.org/abs/2308.08269
Autor:
Zhou, Xinrui, Huang, Yuhao, Xue, Wufeng, Yang, Xin, Zou, Yuxin, Ying, Qilong, Zhang, Yuanji, Liu, Jia, Ren, Jie, Ni, Dong
Localization of the narrowest position of the vessel and corresponding vessel and remnant vessel delineation in carotid ultrasound (US) are essential for carotid stenosis grading (CSG) in clinical practice. However, the pipeline is time-consuming and
Externí odkaz:
http://arxiv.org/abs/2306.02548
Autor:
Huang, Yuhao, Yang, Xin, Huang, Xiaoqiong, Zhou, Xinrui, Chi, Haozhe, Dou, Haoran, Hu, Xindi, Wang, Jian, Deng, Xuedong, Ni, Dong
Deep classifiers may encounter significant performance degradation when processing unseen testing data from varying centers, vendors, and protocols. Ensuring the robustness of deep models against these domain shifts is crucial for their widespread cl
Externí odkaz:
http://arxiv.org/abs/2306.02544
Autor:
Huang, Yuhao, Yang, Xin, Liu, Lian, Zhou, Han, Chang, Ao, Zhou, Xinrui, Chen, Rusi, Yu, Junxuan, Chen, Jiongquan, Chen, Chaoyu, Liu, Sijing, Chi, Haozhe, Hu, Xindi, Yue, Kejuan, Li, Lei, Grau, Vicente, Fan, Deng-Ping, Dong, Fajin, Ni, Dong
The Segment Anything Model (SAM) is the first foundation model for general image segmentation. It has achieved impressive results on various natural image segmentation tasks. However, medical image segmentation (MIS) is more challenging because of th
Externí odkaz:
http://arxiv.org/abs/2304.14660