Medical imaging techniques allow people to observe the internal part of the body without invasive procedure so that several diagnostic methods are developed based on computer vision techniques. Our main question is "How to model the target organs or anatomical structure?" where the model represents the quantitative shape, relationship, or interaction which can be an evaluation standard for the medical application. To achieve the fine quality of the resulting model, we utilize various computer graphics techniques including model deformation, visualization, and machine learning. We also interest in developing and optimizing the imaging techniques for the 3D biomedical image.

Virtual reality technology provides three key features: immersion, interaction, and imagination. Existing VR systems can generate realistic visual and auditory feedback, relatively low concern with haptic feedback. Since, the haptic technology delivers the physical (kinesthetic, tactile) properties of the virtual object via the haptic device, then the human can understand and pursue the complex operation such as the surgical simulation. Our primary research interest is the VR-based training simulator as well as the haptics with real-time physics simulation.

We can find significant and quantified information from the disordered dataset with an innovative data visualization technique. We mainly focused on handling biomedical data and its visualization method.