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20212025
most citedSegment Anything Model for Medical Images?

502 citations · 506 across the 13 of their papers we have counts for

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6 papers · 1 filter

eess.IV2025★ 2 cited

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,…

eess.IV2023

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…

eess.IV2023

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…

eess.IV2023★ 502 cited

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…

eess.IV2022

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…

eess.IV2021★ 1 cited

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…