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A method for robust segmentation of arbitrarily shaped radiopaque structures in cone‐beam CT projections
Author(s) -
Poulsen Per Rugaard,
Fledelius Walther,
Keall Paul J.,
Weiss Elisabeth,
Lu Jun,
Brackbill Emily,
Hugo Geoffrey D.
Publication year - 2011
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3555295
Subject(s) - segmentation , fiducial marker , artificial intelligence , computer vision , cone beam computed tomography , medical imaging , projection (relational algebra) , computer science , image segmentation , medicine , radiology , computed tomography , algorithm
Purpose: Implanted markers are commonly used in radiotherapy for x‐ray based target localization. The projected marker position in a series of cone‐beam CT (CBCT) projections can be used to estimate the three dimensional (3D) target trajectory during the CBCT acquisition. This has important applications in tumor motion management such as motion inclusive, gating, and tumor tracking strategies. However, for irregularly shaped markers, reliable segmentation is challenged by large variations in the marker shape with projection angle. The purpose of this study was to develop a semiautomated method for robust and reliable segmentation of arbitrarily shaped radiopaque markers in CBCT projections.Methods: The segmentation method involved the following three steps: (1) Threshold based segmentation of the marker in three to six selected projections with large angular separation, good marker contrast, and uniform background; (2) construction of a 3D marker model by coalignment and backprojection of the threshold‐based segmentations; and (3) construction of marker templates at all imaging angles by projection of the 3D model and use of these templates for template‐based segmentation. The versatility of the segmentation method was demonstrated by segmentation of the following structures in the projections from two clinical CBCT scans: (1) Three linear fiducial markers (Visicoil) implanted in or near a lung tumor and (2) an artificial cardiac valve in a lung cancer patient.Results: Automatic marker segmentation was obtained in more than 99.9% of the cases. The segmentation failed in a few cases where the marker was either close to a structure of similar appearance or hidden behind a dense structure (data cable).Conclusions: A robust template‐based method for segmentation of arbitrarily shaped radiopaque markers in CBCT projections was developed.