Open AccessUse of three‐dimensional (3D) optical flow method in mapping 3D anatomic structure and tumor contours across four‐dimensional computed tomography data
Author(s) -
Zhang Geoffrey,
Huang TzungChi,
Guerrero Thomas,
Lin KangPing,
Stevens Craig,
Starkschall George,
Forster Ken
Publication year - 2008
Publication title -
journal of applied clinical medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.83
H-Index - 48
ISSN - 1526-9914
DOI - 10.1120/jacmp.v9i1.2738
Subject(s) - displacement (psychology) , optical flow , voxel , data set , feature (linguistics) , imaging phantom , residual , tomography , nuclear medicine , computer vision , computer science , artificial intelligence , physics , medicine , optics , algorithm , image (mathematics) , psychology , linguistics , philosophy , psychotherapist
A three‐dimensional (3D) optical flow program that includes a multi‐resolution feature has been developed and applied to 3D anatomic structure and gross tumor volume (GTV) contour mapping for four‐dimensional computed tomography (4D CT) data. The present study includes contour mapping for actual CT data sets from 3 patients and also for a thoracic phantom in which the displacement for each voxel was known. Of the CT data sets for the actual patients, one set was used to map lung and GTV contours over all respiration phases, and the other two were studied using only the end inspiration and end expiration phases, in which the displacements between phases were the largest. Including the residual motion in the 4D CT data and motion from table shaking, the optical flow calculation agrees with the known displacement to within 1 mm. Excluding errors not introduced by the optical flow algorithm, agreement for a displacement magnitude of 24 mm can be within 0.1 mm. The mapped contours in 4D CT images of lungs, liver, esophagus, GTV, and other structures for actual patients were acceptable to clinicians. The 3D optical flow program is a good tool for contour mapping of anatomic structure and tumor volume across 4D CT scans. PACS numbers: 87.55.D‐, 87.59.bd