Translational Biophotonics Lab

의광학 연구실

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의광학 연구실은 융합기술을 기반으로 의학, 뇌과학, 생명과학 연구를 위한 새로운 광학 기술 개발에 집중하고 있습니다. 주된 연구분야는 창의적인 광학 센싱 및 영상 기술 및 모바일 기반 의료기기 개발이며, 다양한 질병 모델을 바탕으로 동물 및 임상실험까지의 연계연구를 활발히 진행하고 있습니다. 본 연구실은 논문만을 위한 연구가 아닌 기술 이전 및 창업 등이 용이한 바이오 실용화 연구를 지향하고 있으며, 이를 위해 다양한 국내외 기업들과의 네트워크를 통한 협업을 형성하고 있습니다.
The mission of TBL is to develop innovative bio-instruments that address challenges in medicine, biological and neuroscience research. While the term “bench-to-bedside” is most often associated with translational research process, our objective of changing healthcare service is to not only be translational, but also transformational. In order to accomplish this goal, TBL has pursued an interdisciplinary research integrating photonics, medicine, neuroscience, biology, and multiple engineering fields. Activities of TBL span in a wide range of topics such as multi-scale optical imaging, image-guided tissue engineering, optical neuronal stimulation and mobile-based medical device development. We also endeavor to commercialize mature TBL technologies via licensing or through start-up companies.

Major research field

Optical Imaging, Probe-based Diagnostics, ICT Medical Device, Point-of-Care Diagnostics using Smartphone, Bio Artificial Intelligence

Desired field of research

Futuristic Biomedical Devices

Research Keywords and Topics

The ultimate goal of TBL research is to bring forth successful translation of many optical imaging and biomedical techniques for solving significant biological and health care problems. During past 8 years, endeavors of TBL have established the innovative and trustworthy bio-technologies to address challenges across many health domains. With the accumulated knowledge and engineering solutions at UNIST, our group should be able to explore new frontiers and achieve technical breakthroughs in various research fields including optical imaging, tissue engineering, neuroscience, and personalized medicine.

Research Publications

· Serial optical coherence microscopy for label-free volumetric histopathology, Scientific Reports, vol. 10, pp. 6711, 2020
· Quantitative screening of cervical cancers for low-resource settings: Pilot study of smartphone-based endoscopic VIA using machine learning technique, JMIR mHealth and uHealth, vol. 8, pp. e16467, 2020
· Label‐free optical projection tomography for quantitative three‐dimensional anatomy of mouse embryo, Journal of Biophotonics, vol. 12, no. 7, e201800481, 2019


  • LC. 보건의료
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  • LC0606. u-Health 서비스 관련기술(u-EHR)


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  • BT 분야
  • 보건의료 관련응용
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