activity
20202025
most citedSegment Anything Model for Medical Images?

502 citations · 547 across the 16 of their papers we have counts for

collaborators

17 papers

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…

cs.CV2023

Enhancing Modality-Agnostic Representations via Meta-Learning for Brain Tumor Segmentation

Aishik Konwer, Xiaoling Hu, Joseph Bae +3

In medical vision, different imaging modalities provide complementary information. However, in practice, not all modalities may be available during inference or even training. Prev…

cs.LG2023

BALANCE: Bayesian Linear Attribution for Root Cause Localization

Chaoyu Chen, Hang Yu, Zhichao Lei +6

Root Cause Analysis (RCA) plays an indispensable role in distributed data system maintenance and operations, as it bridges the gap between fault detection and system recovery. Exis…