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20202025
most citedSegment Anything Model for Medical Images?

502 citations · 542 across the 11 of their papers we have counts for

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8 papers · 1 filter

eess.IV2025

Accurate and Efficient Fetal Birth Weight Estimation from 3D Ultrasound

Jian Wang, Qiongying Ni, Hongkui Yu +15

Accurate fetal birth weight (FBW) estimation is essential for optimizing delivery decisions and reducing perinatal mortality. However, clinical methods for FBW estimation are ineff…

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★ 4 cited

Temporal Context Matters: Enhancing Single Image Prediction with Disease Progression Representations

Aishik Konwer, Xuan Xu, Joseph Bae +2

Clinical outcome or severity prediction from medical images has largely focused on learning representations from single-timepoint or snapshot scans. It has been shown that disease…

eess.IV2020

Contrastive Rendering for Ultrasound Image Segmentation

Haoming Li, Xin Yang, Jiamin Liang +12

Ultrasound (US) image segmentation embraced its significant improvement in deep learning era. However, the lack of sharp boundaries in US images still remains an inherent challenge…