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Use of three-dimensional (3D) optical flow method in mapping 3D anatomic structure and tumor contours across four-dimensional computed tomography data.


ABSTRACT: A 3-dimensional (3D) optical flow program that includes a multi-resolution feature has been developed and applied to 3D anatomical structure and gross tumor volume (GTV) contour mapping for 4-dimensional (4D) CT data. The study includes contour mapping for 3 real patient CT data sets, and also for a thoracic phantom in which the displacement for each voxel is known. Of the real patient CT data sets, one set has been used to map contours of lung and GTV over all the respiration phases, while the others were studied using only the end inspiration and end expiration phases, in which the displacement between the phases were the largest. Including the residual motion in the 4D CT data and motion table shaking, the optical flow calculation agrees to within 1 mm with the known displacement. Excluding those errors that are not introduced by optical flow algorithm, the agreement can be within 0.1 mm with a displacement magnitude of 24 mm. The mapped contours of lungs, liver, esophagus, GTV, etc. in real patient 4D CT images were acceptable to clinicians. The 3D optical flow program is a good tool for anatomical structure and tumor volume contour mapping across 4D CT scans.

SUBMITTER: Zhang G 

PROVIDER: S-EPMC5721534 | biostudies-literature | 2008 Feb

REPOSITORIES: biostudies-literature

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Use of three-dimensional (3D) optical flow method in mapping 3D anatomic structure and tumor contours across four-dimensional computed tomography data.

Zhang Geoffrey G   Huang Tzung-Chi TC   Guerrero Thomas T   Lin Kang-Ping KP   Stevens Craig C   Starkschall George G   Forster Ken K  

Journal of applied clinical medical physics 20080205 1


A 3-dimensional (3D) optical flow program that includes a multi-resolution feature has been developed and applied to 3D anatomical structure and gross tumor volume (GTV) contour mapping for 4-dimensional (4D) CT data. The study includes contour mapping for 3 real patient CT data sets, and also for a thoracic phantom in which the displacement for each voxel is known. Of the real patient CT data sets, one set has been used to map contours of lung and GTV over all the respiration phases, while the  ...[more]

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