DOI: 10.5061/dryad.mj76c
title: Data from: Airway segmentation and centerline extraction from thoracic CT – comparison of a new method to state of the art commercialized methods

description: Introduction: Our motivation is increased bronchoscopic diagnostic yield
 and optimized preparation, for navigated bronchoscopy. In navigated
 bronchoscopy, virtual 3D airway visualization is often used to guide a
 bronchoscopic tool to peripheral lesions, synchronized with the real time
 video bronchoscopy. Visualization during navigated bronchoscopy, the
 segmentation time and methods, differs. Time consumption and logistics are
 two essential aspects that need to be optimized when integrating such
 technologies in the interventional room. We compared three different
 approaches to obtain airway centerlines and surface. Method: CT lung
 dataset of 17 patients were processed in Mimics (Materialize, Leuven,
 Belgium), which provides a Basic module and a Pulmonology module (beta
 version) (MPM), OsiriX (Pixmeo, Geneva, Switzerland) and our Tube
 Segmentation Framework (TSF) method. Both MPM and TSF were evaluated with
 reference segmentation. Automatic and manual settings allowed us to
 segment the airways and obtain 3D models as well as the centrelines in all
 datasets. We compared the different procedures by user interactions such
 as number of clicks needed to process the data and quantitative measures
 concerning the quality of the segmentation and centrelines such as total
 length of the branches, number of branches, number of generations, and
 volume of the 3D model. Results: The TSF method was the most automatic,
 while the Mimics Pulmonology Module (MPM) and the Mimics Basic Module
 (MBM) resulted in the highest number of branches. MPM is the software
 which demands the least number of clicks to process the data. We found
 that the freely available OsiriX was less accurate compared to the other
 methods regarding segmentation results. However, the TSF method provided
 results fastest regarding number of clicks. The MPM was able to find the
 highest number of branches and generations. On the other hand, the TSF is
 fully automatic and it provides the user with both segmentation of the
 airways and the centerlines. Reference segmentation comparison averages
 and standard deviations for MPM and TSF correspond to literature.
 Conclusion: The TSF is able to segment the airways and extract the
 centerlines in one single step. The number of branches found is lower for
 the TSF method than in Mimics. OsiriX demands the highest number of clicks
 to process the data, the segmentation is often sparse and extracting the
 centerline requires the use of another software system. Two of the
 software systems performed satisfactory with respect to be used in
 preprocessing CT images for navigated bronchoscopy, i.e. the TSF method
 and the MPM. According to reference segmentation both TSF and MPM are
 comparable with other segmentation methods. The level of automaticity and
 the resulting high number of branches plus the fact that both centerline
 and the surface of the airways were extracted, are requirements we
 considered particularly important. The in house method has the advantage
 of being an integrated part of a navigation platform for bronchoscopy,
 whilst the other methods can be considered preprocessing tools to a
 navigation system.
description: Thorax CT patient
 001Thorax CT from 17
 different patients. Metaheader file format.Patient_001.zipThorax CT patient 002Thorax CT from 17 different patients. Metaheader file format.Patient_002.zipThorax CT patient 003Thorax CT from 17 different patients. Metaheader file format.Patient_003.zipThorax CT patient 004Thorax CT from 17 different patients. Metaheader file format.Patient_004.zipThorax CT patient 005Thorax CT from 17 different patients. Metaheader file format.Patient_005.zipThorax CT patient 006Thorax CT from 17 different patients. Metaheader file format.Patient_006.zipThorax CT patient 007Thorax CT from 17 different patients. Metaheader file format.Patient_007.zipThorax CT patient 008Thorax CT from 17 different patients. Metaheader file format.Patient_008.zipThorax CT patient 009Thorax CT from 17 different patients. Metaheader file format.Patient_009.zipThorax CT patient 009Thorax CT from 17 different patients. Metaheader file format.Patient_009.zipThorax CT patient 010Thorax CT from 17 different patients. Metaheader file format.Patient_010.zipThorax CT patient 011Thorax CT from 17 different patients. Metaheader file format.Patient_011.zipThorax CT patient 012Thorax CT from 17 different patients. Metaheader file format.Patient_012.zipThorax CT patient 013Thorax CT from 17 different patients. Metaheader file format.Patient_013.zipThorax CT patient 014Thorax CT from 17 different patients. Metaheader file format.Patient_014.zipThorax CT patient 015Thorax CT from 17 different patients. Metaheader file format.Patient_015.zipThorax CT patient 016Thorax CT from 17 different patients. Metaheader file format.Patient_016.zipThorax CT patient 017Thorax CT from 17 different patients. Metaheader file format.Patient_017.zip