Multi-IMU with Online Self-Consistency for Freehand 3D Ultrasound Reconstruction

no code implementations • 28 Jun 2023 • Mingyuan Luo, Xin Yang, Zhongnuo Yan, Junyu Li, Yuanji Zhang, Jiongquan Chen, Xindi Hu, Jikuan Qian, Jun Cheng, Dong Ni

Ultrasound (US) imaging is a popular tool in clinical diagnosis, offering safety, repeatability, and real-time capabilities.

Agent with Tangent-based Formulation and Anatomical Perception for Standard Plane Localization in 3D Ultrasound

no code implementations • 1 Jul 2022 • Yuxin Zou, Haoran Dou, Yuhao Huang, Xin Yang, Jikuan Qian, Chaojiong Zhen, Xiaodan Ji, Nishant Ravikumar, Guoqiang Chen, Weijun Huang, Alejandro F. Frangi, Dong Ni

First, we formulate SP localization in 3D US as a tangent-point-based problem in RL to restructure the action space and significantly reduce the search space.

Anatomy Reinforcement Learning (RL)

HASA: Hybrid Architecture Search with Aggregation Strategy for Echinococcosis Classification and Ovary Segmentation in Ultrasound Images

no code implementations • 14 Apr 2022 • Jikuan Qian, Rui Li, Xin Yang, Yuhao Huang, Mingyuan Luo, Zehui Lin, Wenhui Hong, Ruobing Huang, Haining Fan, Dong Ni, Jun Cheng

The hybrid framework consists of a pre-trained backbone and several searched cells (i. e., network building blocks), which takes advantage of the strengths of both NAS and the expert knowledge from existing convolutional neural networks.

Image Classification Neural Architecture Search +1

Searching Collaborative Agents for Multi-plane Localization in 3D Ultrasound

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.

Diagnostic Multi-agent Reinforcement Learning +1

Learn Fine-grained Adaptive Loss for Multiple Anatomical Landmark Detection in Medical Images

no code implementations • 19 May 2021 • Guang-Quan Zhou, Juzheng Miao, Xin Yang, Rui Li, En-Ze Huo, Wenlong Shi, Yuhao Huang, Jikuan Qian, Chaoyu Chen, Dong Ni

Our proposed framework is general and shows the potential to improve the efficiency of anatomical landmark detection.

Anatomical Landmark Detection Anatomy +2

Agent with Warm Start and Adaptive Dynamic Termination for Plane Localization in 3D Ultrasound

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.

Deep Reinforcement Learning Reinforcement Learning (RL)

Searching Collaborative Agents for Multi-plane Localization in 3D Ultrasound

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.

Diagnostic Multi-agent Reinforcement Learning +1

FetusMap: Fetal Pose Estimation in 3D Ultrasound

no code implementations • 11 Oct 2019 • Xin Yang, Wenlong Shi, Haoran Dou, Jikuan Qian, Yi Wang, Wufeng Xue, Shengli Li, Dong Ni, Pheng-Ann Heng

(i) This is the first work about 3D pose estimation of fetus in the literature.

3D Pose Estimation Self-Supervised Learning

Agent with Warm Start and Active Termination for Plane Localization in 3D Ultrasound

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.

Reinforcement Learning Reinforcement Learning (RL)