Computational Intelligence in Biomedical Imaging Lab

The long-term goal of the laboratory’s research is to develop computational-intelligence technologies that learn, from data and examples, experts’ knowledge and skills in understanding images in order to make smart decisions.

Computer -aided Systems

Machine/Data Learning

Image Processing & Analysis

Cancer Research

Biomedical Imaging

Prevention & Diagnosis

Lab Vision

Principal Investigator

The research interests of the Computational Intelligence in Biomedical Imaging Laboratory lie in interdisciplinary research in computer engineering and biomedicine, with its primary focuses on machine and data learning in biomedical imaging, computer-aided diagnosis and therapy, and intelligent biomedical image processing and analysis. The long-term goal of the laboratory’s research is to develop computational-intelligence technologies that learn, from data and examples, experts’ knowledge and skills in understanding images in order to make smart decisions. In the computer-aided diagnosis area, computational-intelligence systems learn to detect and diagnose lesions in biomedical images to assist physicians in their biomedical decision making.

In the image-analysis area, computational-intelligence systems learn to trace the boundary of an organ determined by an experienced physician. In the image-processing area, computational-intelligence systems learn to model the image-processing algorithm that separates bones from soft tissue in x-ray projection images. To approach our goal, we believe that creations of and innovations with sophisticated technologies, their theoretical supports, and an understanding of people’s decision-making process and of the human visual system are essential. We are making efforts to “weave” the technological sciences and biomedical sciences into a new paradigm to contribute to both computer science/engineering and biomedicine. We hope that our research will contribute to the understanding of the human visual system, and that our systems will improve people’s health and welfare, and enrich our life and society.

Featured Topics


  • 2014 Best Paper Award from IEICE

  • HealthImaging coverage

  • Flat lesion in CT colonography

  • Virtual dual-energy chest imaging

  • CADx for lung nodules

  • CAD for coronary stenosis