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DOI: 10.1148/rg.252045070
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New Tools for Computer Assistance in Thoracic CT. Part 1. Functional Analysis of Lungs, Lung Lobes, and Bronchopulmonary Segments1

Jan-Martin Kuhnigk, Dipl CS, Volker Dicken, PhD, Stephan Zidowitz, PhD, Lars Bornemann, Dipl CS, Bernd Kuemmerlen, Dipl Phys, Stefan Krass, PhD, Heinz-Otto Peitgen, PhD, Silja Yuval, Hans-Holger Jend, MD, Wigbert S. Rau, MD and Tobias Achenbach, MD

1 From the MeVis Center for Medical Diagnostic Systems and Visualization, Universitaetsallee 29, 28359 Bremen, Germany ( J.M.K., V.D., S.Z., L.B., B.K., S.K., H.O.P.); the Center for Radiology, Hospital Bremen—East, Germany (S.Y., H.H.J.); the Department of Diagnostic Radiology, University Hospital Giessen, Germany (W.S.R.); and the Department of Radiology, University Mainz, Germany (T.A.). Presented as an infoRAD exhibit at the 2003 RSNA Scientific Assembly. Received April 7, 2004; revision requested June 30 and received August 20; accepted September 10. Supported by grant 01EZ0010 from the German Federal Ministry of Education and Research. All authors have no financial relationships to disclose.


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  		Figure 1.  User interface of MeVisPULMO during verification and refinement of the lobar segmentation. The segmented regions are represented by colored overlays on sagittal (left), coronal (middle), and axial (right) images.

 


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  		Figure 2.  Image produced with 3D surface rendering shows the segmented bronchial tree with color coding of the classified segmental bronchi. Each branch can be selected by using the mouse to change the classification of subtrees manually.

 


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  		Figure 3.  Image showing the vascular distances (left) and original image with the blood vessels masked out (right). Weighted addition of the information from these two images produces a combined image (middle), which allows more robust detection of lobar boundaries.

 


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  		Figure 4.  Axial CT image shows the results of estimation of the segments, which are represented by colored overlays with white boundary lines.

 




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