Zobrazeno 1 - 10
of 91
pro vyhledávání: '"Chen, Rusi"'
Autor:
Yu, Junxuan, Chen, Rusi, Zhou, Yongsong, Chen, Yanlin, Duan, Yaofei, Huang, Yuhao, Zhou, Han, Tao, Tan, Yang, Xin, Ni, Dong
Echocardiography video is a primary modality for diagnosing heart diseases, but the limited data poses challenges for both clinical teaching and machine learning training. Recently, video generative models have emerged as a promising strategy to alle
Externí odkaz:
http://arxiv.org/abs/2407.21490
Fine-grained spatio-temporal learning is crucial for freehand 3D ultrasound reconstruction. Previous works mainly resorted to the coarse-grained spatial features and the separated temporal dependency learning and struggles for fine-grained spatio-tem
Externí odkaz:
http://arxiv.org/abs/2407.04242
Autor:
Wang, Jian, Yang, Xin, Jia, Xiaohong, Xue, Wufeng, Chen, Rusi, Chen, Yanlin, Zhu, Xiliang, Liu, Lian, Cao, Yan, Zhou, Jianqiao, Ni, Dong, Gu, Ning
Thyroid nodule classification and segmentation in ultrasound images are crucial for computer-aided diagnosis; however, they face limitations owing to insufficient labeled data. In this study, we proposed a multi-view contrastive self-supervised metho
Externí odkaz:
http://arxiv.org/abs/2402.11497
Autor:
Chen, Chaoyu, Yang, Xin, Chen, Rusi, Yu, Junxuan, Du, Liwei, Wang, Jian, Hu, Xindi, Cao, Yan, Liu, Yingying, Ni, Dong
Ultrasound (US) image segmentation is an active research area that requires real-time and highly accurate analysis in many scenarios. The detect-to-segment (DTS) frameworks have been recently proposed to balance accuracy and efficiency. However, exis
Externí odkaz:
http://arxiv.org/abs/2308.13790
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:
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
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
Publikováno v:
In Medical Image Analysis February 2024 92
Akademický článek
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Autor:
Yu, Guangzheng, Liu, Chengquan, Tang, Bo, Chen, Rusi, Lu, Liu, Cui, Chaoyue, Hu, Yue, Shen, Lingxu, Muyeen, S.M.
Publikováno v:
In Renewable Energy November 2022 199:599-612
Akademický článek
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