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

THIS WEBPAGE IS DEPRECATED - please visit our new website

M. Feuerstein, T. Kitasaka, K. Mori
Adaptive Branch Tracing and Image Sharpening for Airway Tree Extraction in 3-D Chest CT
Second International Workshop on Pulmonary Image Analysis, September 2009 (bib)

The automated extraction of the airway tree from 3-D chest CT data can greatly reduce the workload of physicians during diagnosis (e.g. quantification of airway morphology) and treatment (computer-aided bronchoscopy) of lung disease. This paper presents a method to automatically extract the airways driven by a sharpening filter, which enhances the branch edges in the input image based on the Laplacian of Gaussian, and adaptive cuboidal volumes of interest that an adaptive region growing algorithm uses to trace the airway tree. The method was trained on 20 data sets and evaluated on another 20 data sets from various scanners, using a wide range of acquisition and reconstruction parameters, including low dose scans. Compared to other state-of-the-art methods, our algorithm features the highest detection and extraction rates of bronchial branches. Future research needs to focus on the development of a method for automatic leakage detection.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each authors copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Edit | Attach | Refresh | Diffs | More | Revision r1.13 - 30 Jan 2019 - 15:16 - LeslieCasas

Lehrstuhl für Computer Aided Medical Procedures & Augmented Reality    rss.gif