no code implementations • 30 Oct 2023 • Chaoyu Chen, Xin Yang, Yuhao Huang, Wenlong Shi, Yan Cao, Mingyuan Luo, Xindi Hu, Lei Zhue, Lequan Yu, Kejuan Yue, Yuanji Zhang, Yi Xiong, Dong Ni, Weijun Huang
However, accurately estimating the 3D fetal pose in US volume has several challenges, including poor image quality, limited GPU memory for tackling high dimensional data, symmetrical or ambiguous anatomical structures, and considerable variations in fetal poses.
no code implementations • 24 Jul 2023 • Pan Tan, Mingchen Li, Yuanxi Yu, Fan Jiang, Lirong Zheng, Banghao Wu, Xinyu Sun, Liqi Kang, Jie Song, Liang Zhang, Yi Xiong, Wanli Ouyang, Zhiqiang Hu, Guisheng Fan, Yufeng Pei, Liang Hong
Designing protein mutants of both high stability and activity is a critical yet challenging task in protein engineering.
no code implementations • 29 Dec 2022 • Mingchen Li, Liqi Kang, Yi Xiong, Yu Guang Wang, Guisheng Fan, Pan Tan, Liang Hong
Here, we develop SESNet, a supervised deep-learning model to predict the fitness for protein mutants by leveraging both sequence and structure information, and exploiting attention mechanism.
no code implementations • 23 Jul 2022 • Song Li, Song Ke, Chenxing Yang, Jun Chen, Yi Xiong, Lirong Zheng, Hao liu, Liang Hong
Gonadotrophin-releasing hormone receptor (GnRH1R) is a promising therapeutic target for the treatment of uterine diseases.
no code implementations • 1 Jul 2022 • Jiamin Liang, Xin Yang, Yuhao Huang, Kai Liu, Xinrui Zhou, Xindi Hu, Zehui Lin, Huanjia Luo, Yuanji Zhang, Yi Xiong, Dong Ni
First, leveraging the advantages of self- and fully-supervised learning, our proposed system is trained in weakly-supervised manner for keypoint detection.
no code implementations • 1 Jul 2022 • Chaoyu Chen, Xin Yang, Ruobing Huang, Xindi Hu, Yankai Huang, Xiduo Lu, Xinrui Zhou, Mingyuan Luo, Yinyu Ye, Xue Shuang, Juzheng Miao, Yi Xiong, Dong Ni
In this work, we propose to revisit the classic regression tasks with novel investigations on directly optimizing the fine-grained correlation losses.
no code implementations • 6 Sep 2021 • Yi Xiong, Zhongkui Li
In the scrambling phase, each agent is required to generate some perturbation signals and add them to the edges leading out of it.
no code implementations • 11 Aug 2021 • Shuangchi He, Zehui Lin, Xin Yang, Chaoyu Chen, Jian Wang, Xue Shuang, Ziwei Deng, Qin Liu, Yan Cao, Xiduo Lu, Ruobing Huang, Nishant Ravikumar, Alejandro Frangi, Yuanji Zhang, Yi Xiong, Dong Ni
In this study, we build a novel multi-label learning (MLL) scheme to identify multiple standard planes and corresponding anatomical structures of fetus simultaneously.
no code implementations • 31 Jul 2021 • Ningyuan Chen, Xuefeng Gao, Yi Xiong
It has been recently shown in the literature that the sample averages from online learning experiments are biased when used to estimate the mean reward.
no code implementations • 8 Jul 2021 • Yi Xiong, Ningyuan Chen, Xuefeng Gao, Xiang Zhou
We study the model-based undiscounted reinforcement learning for partially observable Markov decision processes (POMDPs).
no code implementations • 22 May 2021 • Xin Yang, Yuhao Huang, Ruobing Huang, Haoran Dou, Rui Li, Jikuan Qian, Xiaoqiong Huang, Wenlong Shi, Chaoyu Chen, Yuanji Zhang, Haixia Wang, Yi Xiong, Dong Ni
First, our proposed method is general and it can accurately localize multiple SPs in different challenging US datasets.
Multi-agent Reinforcement Learning Neural Architecture Search
1 code implementation • 26 Mar 2021 • Xin Yang, Haoran Dou, Ruobing Huang, Wufeng Xue, Yuhao Huang, Jikuan Qian, Yuanji Zhang, Huanjia Luo, Huizhi Guo, Tianfu Wang, Yi Xiong, Dong Ni
2D US has to perform scanning for each SP, which is time-consuming and operator-dependent.
no code implementations • 11 Jan 2021 • Zhendong Liu, Xiaoqiong Huang, Xin Yang, Rui Gao, Rui Li, Yuanji Zhang, Yankai Huang, Guangquan Zhou, Yi Xiong, Alejandro F Frangi, Dong Ni
Deep segmentation models that generalize to images with unknown appearance are important for real-world medical image analysis.
no code implementations • 30 Jul 2020 • Yuhao Huang, Xin Yang, Rui Li, Jikuan Qian, Xiaoqiong Huang, Wenlong Shi, Haoran Dou, Chaoyu Chen, Yuanji Zhang, Huanjia Luo, Alejandro Frangi, Yi Xiong, Dong Ni
In this study, we propose a novel Multi-Agent Reinforcement Learning (MARL) framework to localize multiple uterine SPs in 3D US simultaneously.
Multi-agent Reinforcement Learning Neural Architecture Search
no code implementations • 1 Apr 2020 • Chaoyu Chen, Xin Yang, Ruobing Huang, Wenlong Shi, Shengfeng Liu, Mingrong Lin, Yuhao Huang, Yong Yang, Yuanji Zhang, Huanjia Luo, Yankai Huang, Yi Xiong, Dong Ni
The performance of the proposed framework is evaluated on a 3D US dataset to detect five key fetal facial landmarks.
no code implementations • 14 Feb 2020 • Zhendong Liu, Xin Yang, Rui Gao, Shengfeng Liu, Haoran Dou, Shuangchi He, Yuhao Huang, Yankai Huang, Huanjia Luo, Yuanji Zhang, Yi Xiong, Dong Ni
In this paper, we propose a novel and intuitive framework to remove the appearance shift, and hence improve the generalization ability of DNNs.
no code implementations • NeurIPS 2021 • Xiang Zhou, Yi Xiong, Ningyuan Chen, Xuefeng Gao
We study a multi-armed bandit problem where the rewards exhibit regime switching.
1 code implementation • 10 Oct 2019 • Haoran Dou, Xin Yang, Jikuan Qian, Wufeng Xue, Hao Qin, Xu Wang, Lequan Yu, Shujun Wang, Yi Xiong, Pheng-Ann Heng, Dong Ni
In this study, we propose a novel reinforcement learning (RL) framework to automatically localize fetal brain standard planes in 3D US.