activity
20192023
most citedLearn Fine-grained Adaptive Loss for Multiple Anatomical Landmark Detection in Medical Images

28 citations · 40 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2023

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…

cs.CV2022

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

Yuxin Zou, Haoran Dou, Yuhao Huang +9

Standard plane (SP) localization is essential in routine clinical ultrasound (US) diagnosis. Compared to 2D US, 3D US can acquire multiple view planes in one scan and provide compl…

cs.CV2022

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…

cs.CV2021★ 4 cited

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

Xin Yang, Yuhao Huang, Ruobing Huang +10

3D ultrasound (US) has become prevalent due to its rich spatial and diagnostic information not contained in 2D US. Moreover, 3D US can contain multiple standard planes (SPs) in one…

cs.CV2021★ 28 cited

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

Guang-Quan Zhou, Juzheng Miao, Xin Yang +7

Automatic and accurate detection of anatomical landmarks is an essential operation in medical image analysis with a multitude of applications. Recent deep learning methods have imp…

eess.IV2021

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

Xin Yang, Haoran Dou, Ruobing Huang +9

Accurate standard plane (SP) localization is the fundamental step for prenatal ultrasound (US) diagnosis. Typically, dozens of US SPs are collected to determine the clinical diagno…

cs.CV2020★ 4 cited

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

Yuhao Huang, Xin Yang, Rui Li +10

3D ultrasound (US) is widely used due to its rich diagnostic information, portability and low cost. Automated standard plane (SP) localization in US volume not only improves effici…

cs.CV2019★ 1 cited

FetusMap: Fetal Pose Estimation in 3D Ultrasound

Xin Yang, Wenlong Shi, Haoran Dou +6

The 3D ultrasound (US) entrance inspires a multitude of automated prenatal examinations. However, studies about the structuralized description of the whole fetus in 3D US are still…

eess.IV2019★ 3 cited

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

Haoran Dou, Xin Yang, Jikuan Qian +8

Standard plane localization is crucial for ultrasound (US) diagnosis. In prenatal US, dozens of standard planes are manually acquired with a 2D probe. It is time-consuming and oper…