Publications

Conference Papers

Segmenting What Matters: A Dual-Stage Active Learning Framework for Weakly Supervised Breast Ultrasound Segmentation
Nuojunxi Zhang (First Author), Kuan Huang (Advisor)
IEEE International Conference on Bioinformatics and Biomedicine (IEEE-BIBM 2025)
Status: Accepted

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Presentations

Poster: Medical Computer Vision for Parkinson’s Rehabilitation
Nuojunxi Zhang (Presenter)
Research Day – Wenzhou-Kean University, April 2023

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Research Impact & Future Work

My research focuses on developing practical AI solutions for medical imaging that reduce annotation burden while maintaining clinical accuracy. Current work explores active learning strategies for ultrasound segmentation with promising preliminary results.

Research Interests:

• Weakly supervised learning in medical imaging
• Active learning for computer vision
• AI applications in healthcare diagnostics
• Synthetic data generation for medical AI