名古屋大学 · 医学
茅原賢作教授の研究室では、3次元胸部CT画像を用いた気管支構造の自動抽出と解剖的ラベリングに注力しています。特に、仮想気管支鏡（VBS）や画像支援診断システムの実現に向けて、画像認識と知識ベースを統合した高度な画像解析技術を開発しています。研究の柱は、正確な気管支分岐構造の自動識別と、臨床応用に向けた信頼性の高い画像処理アルゴリズムの構築です。
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
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