Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

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H. Yano, M. Feuerstein, T. Kitasaka, K. Mori
Study on bronchus region extraction from 3D chest CT images using local intensity structure analysis
18th Meeting of the Japan Society of Computer Assisted Surgery, Tokyo, Japan, November 2009 (bib)

This paper presents a method for extracting bronchus regions from 3D chest CT images. Several research groups have proposed methods for extracting bronchus regions by using region growing algorithm. However, these methods do not work well in the case of tumors divide the bronchial tree into several parts. Therefore, this paper proposes a method that can extract the bronchus region in such cases using local intensity structure analysis, CT value distribution and shape features. First, the proposed method extracts cylindrical structures by using the hessian matrix to analyze local intensity structures. Second, we extract tube structures by using a modified RRF (Radial Reach Filter) to analyze CT value distributions and shape features. Finally, we extract the bronchus regions by combining the result of hessian analysis and RRF. We applied the proposed method to four 3D chest CT datasets. Experimental results showed that this method can extract well in the case of tumors dividing the bronchial tree.
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