Beyond the Conventional, Pioneering the Unexplored.
지능형 생체신호처리 연구실 · 경북대학교 전자공학부
We develop intelligent signal processing and AI for medical ultrasound and biomedical imaging, from physics-informed reconstruction and unsupervised deep beamforming to wearable and robotic ultrasound systems that run in real time on edge devices.
Segmentation/detection-based automation of clinically relevant parameter measurement, and robust, trustworthy medical AI with calibration and uncertainty, controllability, and generalization for real clinical workflows.
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Physics-informed neural networks that embed wave propagation, beamforming, and image-formation models into self-/unsupervised learning for high-fidelity ultrasound reconstruction, physics-guided inverse modeling for artifact reduction, and learning-based quantitative and perfusion ultrasound.
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Closed-loop robotic ultrasound guidance with active scanning policies, self-supervised adaptation across operators, devices, and patients, and data-/compute-efficient learning with hardware-aware design for edge devices.
Learn more →Our paper "Non-invasive and continuous blood flow monitoring system using a wearable cross-shaped ultrasound array" (first author: Hyunwoo Cho) has been accepted for publication in IEEE Transactions on Instrumentation and Measurement (IF 7.0, JCR top 5.6%). Congratulations to all co-authors!
Wonjun Jang and Yeonwoo Ji have joined IBSP Lab. as undergraduate researchers. Welcome aboard!
The Intelligent Biomedical Signal Processing Laboratory has been launched in the School of Electronics Engineering, KNU. We are recruiting new members!
