activity
20232026
most citedOne-Stop Automated Diagnostic System for Carpal Tunnel Syndrome in Ultrasound Images Using Deep Learning

14 citations · 15 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

PromptGate Client Adaptive Vision Language Gating for Open Set Federated Active Learning

Adea Nesturi, David Dueñas Gaviria, Jiajun Zeng +1

Deploying medical AI across resource-constrained institutions demands data-efficient learning pipelines that respect patient privacy. Federated Learning (FL) enables collaborative…

cs.CV2026

K-MaT: Knowledge-Anchored Manifold Transport for Cross-Modal Prompt Learning in Medical Imaging

Jiajun Zeng, Shadi Albarqouni

Large-scale biomedical vision-language models (VLMs) adapted on high-end imaging (e.g., CT) often fail to transfer to frontline low-end modalities (e.g., radiography), collapsing i…

cs.CV2024

EM-Net: Efficient Channel and Frequency Learning with Mamba for 3D Medical Image Segmentation

Ao Chang, Jiajun Zeng, Ruobing Huang +1

Convolutional neural networks have primarily led 3D medical image segmentation but may be limited by small receptive fields. Transformer models excel in capturing global relationsh…

eess.IV2024

Is Two-shot All You Need? A Label-efficient Approach for Video Segmentation in Breast Ultrasound

Jiajun Zeng, Dong Ni, Ruobing Huang

Breast lesion segmentation from breast ultrasound (BUS) videos could assist in early diagnosis and treatment. Existing video object segmentation (VOS) methods usually require dense…

eess.IV2024★ 14 cited

One-Stop Automated Diagnostic System for Carpal Tunnel Syndrome in Ultrasound Images Using Deep Learning

Jiayu Peng, Jiajun Zeng, Manlin Lai +3

Objective: Ultrasound (US) examination has unique advantages in diagnosing carpal tunnel syndrome (CTS) while identifying the median nerve (MN) and diagnosing CTS depends heavily o…

cs.CV2023★ 1 cited

PE-MED: Prompt Enhancement for Interactive Medical Image Segmentation

Ao Chang, Xing Tao, Xin Yang +5

Interactive medical image segmentation refers to the accurate segmentation of the target of interest through interaction (e.g., click) between the user and the image. It has been w…