502 citations · 506 across the 13 of their papers we have counts for
13 papers
MoNetV2: Enhanced Motion Network for Freehand 3D Ultrasound Reconstruction
Mingyuan Luo, Xin Yang, Zhongnuo Yan +8
Three-dimensional (3D) ultrasound (US) aims to provide sonographers with the spatial relationships of anatomical structures, playing a crucial role in clinical diagnosis. Recently,…
UniUSNet: A Promptable Framework for Universal Ultrasound Disease Prediction and Tissue Segmentation
Zehui Lin, Zhuoneng Zhang, Xindi Hu +5
Ultrasound is widely used in clinical practice due to its affordability, portability, and safety. However, current AI research often overlooks combined disease prediction and tissu…
FetusMapV2: Enhanced Fetal Pose Estimation in 3D Ultrasound
Chaoyu Chen, Xin Yang, Yuhao Huang +11
Fetal pose estimation in 3D ultrasound (US) involves identifying a set of associated fetal anatomical landmarks. Its primary objective is to provide comprehensive information about…
FFPN: Fourier Feature Pyramid Network for Ultrasound Image Segmentation
Chaoyu Chen, Xin Yang, Rusi Chen +7
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 be…
Multi-IMU with Online Self-Consistency for Freehand 3D Ultrasound Reconstruction
Mingyuan Luo, Xin Yang, Zhongnuo Yan +7
Ultrasound (US) imaging is a popular tool in clinical diagnosis, offering safety, repeatability, and real-time capabilities. Freehand 3D US is a technique that provides a deeper un…
Fourier Test-time Adaptation with Multi-level Consistency for Robust Classification
Yuhao Huang, Xin Yang, Xiaoqiong Huang +7
Deep classifiers may encounter significant performance degradation when processing unseen testing data from varying centers, vendors, and protocols. Ensuring the robustness of deep…
Segment Anything Model for Medical Images?
Yuhao Huang, Xin Yang, Lian Liu +16
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. Howev…
Online Reflective Learning for Robust Medical Image Segmentation
Yuhao Huang, Xin Yang, Xiaoqiong Huang +7
Deep segmentation models often face the failure risks when the testing image presents unseen distributions. Improving model robustness against these risks is crucial for the large-…
Weakly-supervised High-fidelity Ultrasound Video Synthesis with Feature Decoupling
Jiamin Liang, Xin Yang, Yuhao Huang +8
Ultrasound (US) is widely used for its advantages of real-time imaging, radiation-free and portability. In clinical practice, analysis and diagnosis often rely on US sequences rath…
Fine-grained Correlation Loss for Regression
Chaoyu Chen, Xin Yang, Ruobing Huang +10
Regression learning is classic and fundamental for medical image analysis. It provides the continuous mapping for many critical applications, like the attribute estimation, object…
Sketch guided and progressive growing GAN for realistic and editable ultrasound image synthesis
Jiamin Liang, Xin Yang, Yuhao Huang +7
Ultrasound (US) imaging is widely used for anatomical structure inspection in clinical diagnosis. The training of new sonographers and deep learning based algorithms for US image a…
Self Context and Shape Prior for Sensorless Freehand 3D Ultrasound Reconstruction
Mingyuan Luo, Xin Yang, Xiaoqiong Huang +6
3D ultrasound (US) is widely used for its rich diagnostic information. However, it is criticized for its limited field of view. 3D freehand US reconstruction is promising in addres…
Joint Landmark and Structure Learning for Automatic Evaluation of Developmental Dysplasia of the Hip
Xindi Hu, Limin Wang, Xin Yang +9
The ultrasound (US) screening of the infant hip is vital for the early diagnosis of developmental dysplasia of the hip (DDH). The US diagnosis of DDH refers to measuring alpha and…