To provide higher dimensional medical data to support diagnosis and treatment, we have developed registration and integration technologies between different types of medical images acquired before and during surgery. We have also developed technology to simultaneously measure the 3D shape, color, and texture of organ surfaces from monocular endoscope images using shape estimation technology based on multifocal images.

3-D Shape Measurement in Endoscopy/Microscopy

Multi-view Ultrasound Image Measurement

3-D Reconstruction of Bone Shape Feature Points from 2-D Cephalograms

We have analyzed human anatomical structures and biological mechanisms by integrating bioinstrumentation technology, computational AI analysis technology, and biological modeling and simulation technology. By utilizing numerical analysis and AI, we have developed systems for abnormality detection and disease state analysis.

Segmentation of Brain Anatomical Structures from MR Images

Respiratory Status Monitoring

Nerve Region Detection from Ultrasound Images

Pulmonary Lesion Analysis from Thoracoscopic Images

Morphometric Analysis of trigeminal nerve

The goal of this study is to build an intelligent database system that effectively integrates and processes huge amounts of medical data obtained from a wide variety of devices used for diagnosis and treatment in the medical field. This system consists of various AI agents that autonomously contact one another, network, and collaborate to process medical data and procedures.

AI of AIs for Medical IoT Applications

We have developed devices that support safer surgical procedures, such as surgical navigation systems using augmented reality (AR) and projection mapping (PM) technologies, and surgical devices using soft materials that change rigidity through pneumatic control.

Projection Mapping for Neurosurgery Assistance

Surgical Navigation Systems and Theoretical Analysis of Their Accuracy

Design of Stiffness-Tunable Materials and and Their Application to Organ Grasping Devices