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 • 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.
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 • 1 Jul 2022 • Mingyuan Luo, Xin Yang, Hongzhang Wang, Liwei Du, Dong Ni
Our contribution is two-fold.
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.
no code implementations • 31 Jul 2021 • Mingyuan Luo, Xin Yang, Xiaoqiong Huang, Yuhao Huang, Yuxin Zou, Xindi Hu, Nishant Ravikumar, Alejandro F Frangi, Dong Ni
In this paper, we propose a novel approach to sensorless freehand 3D US reconstruction considering the complex skill sequences.
no code implementations • 24 Sep 2020 • Xiaoqiong Huang, Zejian Chen, Xin Yang, Zhendong Liu, Yuxin Zou, Mingyuan Luo, Wufeng Xue, Dong Ni
Based on the zero-shot style transfer to remove appearance shift and test-time augmentation to explore diverse underlying anatomy, our proposed method is effective in combating the appearance shift.