Biomedical Signal Processing Laboratory

About Lab

연구실 소개

We are dedicated to advancing biomedical signal processing technologies

Welcome to BSP Lab

Biomedical Signal Processing Laboratory는 모두의연구소(MODULABS)의 공개 연구 소모임입니다. 생체 신호 처리 기술을 연구하고 개발하며, 의료 데이터 분석, 인공지능 기반 진단 시스템, 그리고 웨어러블 헬스케어 기술 분야에서 함께 학습하고 성장하고 있습니다.

본 소모임은 ECG, EEG, EMG 등 다양한 생체 신호의 수집, 처리, 분석을 통해 질병 진단 및 건강 모니터링 시스템을 탐구하고 있으며, 기계학습과 딥러닝 기술을 활용하여 의료 분야의 새로운 가능성을 연구합니다.

💡 가상 오피스로 운영되는 온라인 연구 소모임입니다. 누구나 참여 가능합니다!

Research Projects

Publications

Team Members

Laboratory Image

Research Areas

연구 분야

Our main research focuses and areas of expertise

Biomedical Signal Processing

생체 신호 (심전도, 뇌파, 근전도 등) 처리, 분석 및 질병 진단

Medical Image Processing

의료 영상 (초음파, CT, MRI, X-ray 등) 분석, 세분화 및 질병 검출

Deep Learning for Healthcare

딥러닝 기반 의료 데이터 분석, 진단 및 예측 모델 개발

Wearable Biosensors

웨어러블 센서 기반 생체 신호 측정 및 실시간 모니터링

Medical Ultrasound Imaging

초음파 영상 처리, 빔포밍 및 고화질 이미징 기술

Point-of-Care Devices

휴대용 의료 기기 및 소형 진단 시스템 개발

Team Members

연구원

Meet our talented research team

Lab Members

Hyunwoo Cho, Ph.D.

Lab Director

Postdoctoral Researcher
Department of Electronic Engineering, Sogang University

Research Interests:
Biomedical Signal Processing, Wearable Sensors, AI in Healthcare, Medical Imaging

Join Us!

We're looking for passionate researchers interested in biomedical signal processing and AI in healthcare.

Join Our Research Community

BSP Lab은 생체 신호 처리와 의료 AI에 관심있는 모든 분들을 환영합니다. 학생, 연구자, 엔지니어 등 배경에 관계없이 함께 연구하고 학습할 수 있습니다.

MODULABS에서 신청하기 Contact Us

Publications

Papers & Presentations

Our recent research papers and conference presentations

2025

Intravascular ultrasound imaging with directional synthetic aperture focusing and coherence factor weighting

Cho, H., Lee, J., Park, D., Chang, J., Jang, J., & Yoo, Y.

Ultrasonography, Vol. 44, No. 5, 2025 (in press)

Link

2025

Numerical investigation of optimal transmission-reception conditions for aliasing-free ultrasound localization microscopy

Cho, H., Lee, J., Park, S., & Yoo, Y.

Ultrasonics, Vol. 154, 107704, 2025 (JCR-IF: 4.1, Top 11.0% in Acoustics)

Link

2025

Fully automated bladder volume measurement system using a T-shaped ultrasound probe and free-hand motion-based 3D reconstruction

Park, D., Cho, H., Song, I., Jang, J., & Yoo, Y. (Co-first authorship)

IEEE Access, Vol. 13, 80247, 2025

Link

2025

Deep learning model for CT-based adrenal gland volume determination and normal reference definition in dogs

Park, S., Cho, H., Lee, K., & Yoon, H. (Co-first authorship)

Pakistan Veterinary Journal, Vol. 45, No. 1, 320, 2025 (JCR-IF: 5.4, Top 2.1% in Veterinary Sciences)

Link

2024

Development of a deep learning model for automatic detection of narrowed intervertebral disc space sites in caudal thoracic and lumbar lateral X-ray images of dogs

Park, J., Cho, H., Ji, Y., Lee, K., & Yoon, H. (Co-first authorship)

Frontiers in Veterinary Science, Vol. 11, 1453765, 2024 (JCR-IF: 2.6, Top 12.9% in Veterinary Sciences)

Link

2024

Deep coherence learning: An unsupervised deep beamformer for high quality single plane wave imaging in medical ultrasound

Cho, H., Park, S., Kang, J., & Yoo, Y.

Ultrasonics, Vol. 143, 107408, 2024 (JCR-IF: 3.8, Top 11.2% in Acoustics)

Link

2024

Detection of spondylosis deformans in thoracolumbar and lumbar lateral X-ray images of dogs using a deep learning network

Park, J., Cho, H., Ji, Y., Lee, K., & Yoon, H. (Co-first authorship)

Frontiers in Veterinary Science, Vol. 11, 1334438, 2024 (JCR-IF: 2.6, Top 12.9% in Veterinary Sciences)

Link

2024

A system-on-chip solution for deep learning-based automatic fetal biometric measurement

Cho, H., Kim, D., Chang, S., Kang, J., & Yoo, Y.

Expert Systems with Applications, Vol. 237, 121482, 2024 (JCR-IF: 7.5, Top 7.0% in Engineering, Electrical & Electronic)

Link

2023

A lightweight deep learning network on a system-on-chip for wearable ultrasound bladder volume measurement systems: Preliminary study

Cho, H., Song, I., Jang, J., & Yoo, Y.

Bioengineering, Vol. 10, No. 5, 525, 2023

Link

2022

A deep learning model for CT-based kidney volume determination in dogs and normal reference definition

Ji, Y., Cho, H., Seon, S., Lee, K., & Yoon, H.

Frontiers in Veterinary Science, Vol. 9, 1011804, 2022

Link

2022

Air-coupled ultrasound sealing integrity inspection using leaky lamb waves in a simplified model of a lithium-ion pouch battery: Feasibility study

Cho, H., Kil, E., Jang, J., Kang, J., Song, I., & Yoo, Y.

Sensors, Vol. 22, No. 17, 6718, 2022

Link

2024

An unsupervised deep neural network for reverberation artifact reduction in medical ultrasound

Cho, H., Kang, J., & Yoo, Y.

IEEE Ultrasonics, Ferroelectrics, and Frequency Control Joint Symposium (UFFC-JS), 2024

Oral

2024

An unsupervised deep clutter filter for high-quality ultrafast perfusion imaging

Cho, H., Kang, J., & Yoo, Y.

IEEE Ultrasonics, Ferroelectrics, and Frequency Control Joint Symposium (UFFC-JS), 2024

Oral

2024

An unsupervised deep neural network for reverberation artifact reduction

Cho, H., & Yoo, Y.

The 16th Congress of the Asian Federation of Societies for Ultrasound in Medicine and Biology (AFSUMB), 2024

Oral

2023

An unsupervised deep beamformer for high-quality ultrafast ultrasound imaging

Cho, H., Kang, J., & Yoo, Y.

The 19th World Federation for Ultrasound in Medicine and Biology Congress (WFUMB), 2023

Oral Young Investigator Prize

2023

Deep coherence learning: An unsupervised deep learning framework for high-quality plane wave imaging

Cho, H., Kang, J., & Yoo, Y.

International Symposium on Integrated Medical Solutions (iSims), 2023

Best Poster Award

2023

A self-supervised learning framework for artifact-free high-quality plane wave imaging

Cho, H., & Yoo, Y.

The 54th Annual Congress of Korean Society of Ultrasound in Medicine (KSUM), 2023

Oral Young Investigator Award - Gold

2023

Deep coherence learning: An unsupervised deep learning framework for high-quality single plane wave imaging

Cho, H., Park, S., Kang, J., & Yoo, Y.

IEEE International Ultrasonics Symposium (IUS), 2023

Oral

2022

Residual CNN based angular compounding for high-quality plane wave imaging

Cho, H., Jang, J., & Yoo, Y.

IEEE International Ultrasonics Symposium (IUS), 2022

2020

CNN-based semantic segmentation networks for multiple fetal biometric measurements

Cho, H., Kang, J., Chang, S., & Yoo, Y.

IEEE International Ultrasonics Symposium (IUS), 2020

Research Ideas

Looking for Ideas!

We're exploring various research directions and welcome your ideas

Share Your Research Ideas!

BSP Lab은 생체의학 신호 및 영상 처리 분야의 다양한 연구 아이디어를 탐색하고 있습니다.
함께 연구하고 싶은 주제나 아이디어가 있으신가요?

현재 관심 분야: Medical Ultrasound Imaging, Deep Learning for Healthcare, Wearable Biosensors, Medical Image Analysis

뉴스

Recent updates from our lab

Oct 2025

🎉 BSP Lab Launched!

Biomedical Signal Processing Laboratory가 모두의연구소(MODULABS) 공개 연구 소모임으로 공식 오픈했습니다. 생체 신호 처리와 의료 AI에 관심있는 모든 분들을 환영합니다!

Join us

Get In Touch

연락처

Location

Virtual Office
온라인 기반 가상 연구실
모두의연구소 BSP Lab

Response Time

Within 48 hours
(이메일 문의 시)

Email

[email protected]

Office Hours

Monday - Friday
9:00 AM - 6:00 PM

Biomedical Signal ProcessingLaboratory

연구실 소개

Welcome to BSP Lab

연구 분야

Biomedical Signal Processing

Medical Image Processing

Deep Learning for Healthcare

Wearable Biosensors

Medical Ultrasound Imaging

Point-of-Care Devices

연구원

Lab Members

Hyunwoo Cho, Ph.D.

Join Us!

Join Our Research Community

Papers & Presentations

Intravascular ultrasound imaging with directional synthetic aperture focusing and coherence factor weighting

Numerical investigation of optimal transmission-reception conditions for aliasing-free ultrasound localization microscopy

Fully automated bladder volume measurement system using a T-shaped ultrasound probe and free-hand motion-based 3D reconstruction

Deep learning model for CT-based adrenal gland volume determination and normal reference definition in dogs

Development of a deep learning model for automatic detection of narrowed intervertebral disc space sites in caudal thoracic and lumbar lateral X-ray images of dogs

Deep coherence learning: An unsupervised deep beamformer for high quality single plane wave imaging in medical ultrasound

Detection of spondylosis deformans in thoracolumbar and lumbar lateral X-ray images of dogs using a deep learning network

A system-on-chip solution for deep learning-based automatic fetal biometric measurement

A lightweight deep learning network on a system-on-chip for wearable ultrasound bladder volume measurement systems: Preliminary study

A deep learning model for CT-based kidney volume determination in dogs and normal reference definition

Air-coupled ultrasound sealing integrity inspection using leaky lamb waves in a simplified model of a lithium-ion pouch battery: Feasibility study

An unsupervised deep neural network for reverberation artifact reduction in medical ultrasound

An unsupervised deep clutter filter for high-quality ultrafast perfusion imaging

An unsupervised deep neural network for reverberation artifact reduction

An unsupervised deep beamformer for high-quality ultrafast ultrasound imaging

Deep coherence learning: An unsupervised deep learning framework for high-quality plane wave imaging

A self-supervised learning framework for artifact-free high-quality plane wave imaging

Deep coherence learning: An unsupervised deep learning framework for high-quality single plane wave imaging

Residual CNN based angular compounding for high-quality plane wave imaging

CNN-based semantic segmentation networks for multiple fetal biometric measurements

Looking for Ideas!

Share Your Research Ideas!

뉴스

🎉 BSP Lab Launched!

연락처

Location

Response Time

Email

Office Hours

Send us a message

Biomedical Signal Processing
Laboratory