Welcome to Biomedical
Intelligence Laboratory
The mission of BiLab is to research and develop technologies that assist clinicians, and ultimately improve quality of life. We analyze various data modalities using artificial intelligence(AI) through multidisciplinary research. On the other side, we utilize extended reality(XR) to assist surgery, and perform simulation and training in healthcare. Our research goal is to extend AI and XR technologies to be realized as a medical twin.
Research Overview
- Medical Image
- Biosignal
- Omics Data
- Lifelog Data
- EHR
Medical Twin
- Augmented Reality
- Mixed Reality
- Virtual Reality
Clinical Demonstration
(임상 실증)
Research Areas
Medical Image,
Biosignal,
Lifelog Data,
Genomic Data,
AR assisted Surgery,
VR Medical Simulation & Training
Medical Image Analysis - AI in Healthcare
Medical images account for the majority of medical data, acquired from various imaging equipment such as x-ray, CT, MRI, ultrasonography, endoscopy, etc., as well as all types of images related to patients in medical institute. We analyze medical images from hospitals by applying image processing and deep learning technologies.
Biosignal Analysis - AI in Healthcare
Biosignals indicate health status in real-time. In addition to vital signs from the ORs and the wards, there are signals measured for examination and wearable devices. We analyze biosignals from hospitals and during daily life by applying signal processing and deep learning technologies.
Lifelog Data Analysis - AI in Healthcare
The field of Omics is divided into Genomics & Epigenomics, Transcriptomics, Metabolomics, and Proteomics according to biological aspects. We analyze various biological data from the DNA level for understanding life phenomena to the molecule level for drug discovery by applying deep learning technologies in bioinformatics.
Genomic Data Analysis - AI in Healthcare
Lifelog data is not measured by medical institutions, but includes exercise and healthcare data measured with a mobile phone or IoT sensor during daily life. We analyze lifelog data considering the characteristics by applying machine learning, and deep learning technologies.
AR assisted Surgery - XR in Healthcare
Electronic Health Records(EHR) contain key patient information and can be shared in different healthcare environments. We support clinicians who want to utilize EHR-Common Data Model(CDM), and perform multimodal data research that connects to unstructured data and EHR-CDM.
VR Medical Simulation & Training - XR in Healthcare
The Augmented Reality(AR) technology is utilized to assist the surgery by registration of patient's anatomical structures. We research the segmentation method for 3D anatomical structures from patient images before surgery, and registration method for overlaying on the target position during surgery.
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