2 citations · 5 across the 9 of their papers we have counts for
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Fine-grained Context and Multi-modal Alignment for Freehand 3D Ultrasound Reconstruction
Zhongnuo Yan, Xin Yang, Mingyuan Luo +4
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…
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…
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…
Deep Motion Network for Freehand 3D Ultrasound Reconstruction
Mingyuan Luo, Xin Yang, Hongzhang Wang +2
Freehand 3D ultrasound (US) has important clinical value due to its low cost and unrestricted field of view. Recently deep learning algorithms have removed its dependence on bulky…
HASA: Hybrid Architecture Search with Aggregation Strategy for Echinococcosis Classification and Ovary Segmentation in Ultrasound Images
Jikuan Qian, Rui Li, Xin Yang +8
Different from handcrafted features, deep neural networks can automatically learn task-specific features from data. Due to this data-driven nature, they have achieved remarkable su…
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…