Nagoya University · Medicine
Professor Kensaku Mori's research lab specializes in medical image computing, with a focus on 3D medical image analysis and computer-aided diagnosis systems. The lab develops advanced algorithms for automated anatomical labeling and bronchus extraction from 3D chest CT images, enabling applications in virtual bronchoscopy and lung cancer detection. Key research directions include image segmentation, region growing techniques, and knowledge-based anatomical labeling using rule-based systems. The lab's work bridges medical imaging and clinical decision support, aiming to improve diagnostic accuracy and efficiency in pulmonary disease assessment.
Figures are computed from collected data and may differ slightly.
This paper describes a method for the automated anatomical labeling of the bronchial branch extracted from a three-dimensional (3-D) chest X-ray CT image and its application to a virtual bronchoscopy system (VBS). Automated anatomical labeling is necessary for implementing an advanced computer-aided diagnosis system of 3-D medical images. This method performs the anatomical labeling of the bronchial branch using the knowledge base of the bronchial branch name. The knowledge base holds informatio
In this paper we present a procedure to extract bronchus area from 3D chest X-ray CT images. Extraction of bronchus from chest X-ray CT images is of critical importance for both the computer aided detection of lung cancer and the virtual bronchoscopy system. This procedure consists of three major steps: 1) calculation of a start point for region growing; 2) determination of the optimum threshold value; and 3) final extraction of bronchus area with the optimum threshold value. The proposed proced
Open papers in the app to read, cite, and organize with AI.
