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3D interfractional patient position verification using 2D‐3D registration of orthogonal images
Author(s) -
Jans H.S.,
Syme A. M.,
Rathee S.,
Fallone B. G.
Publication year - 2006
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 - 10.1118/1.2192907
Subject(s) - computer vision , image registration , imaging phantom , artificial intelligence , computer science , position (finance) , preprocessor , rotation (mathematics) , transformation (genetics) , rigid transformation , calibration , mathematics , image (mathematics) , optics , physics , biochemistry , chemistry , statistics , finance , economics , gene
Reproducible positioning of the patient during fractionated external beam radiation therapy is imperative to ensure that the delivered dose distribution matches the planned one. In this paper, we expand on a 2D‐3D image registration method to verify a patient's setup in three dimensions (rotations and translations) using orthogonal portal images and megavoltage digitally reconstructed radiographs (MDRRs) derived from CT data. The accuracy of 2D‐3D registration was improved by employing additional image preprocessing steps and a parabolic fit to interpolate the parameter space of the cost function utilized for registration. Using a humanoid phantom, precision for registration of three‐dimensional translations was found to be better than 0.5 mm (1 s.d.) for any axis when no rotations were present. Three‐dimensional rotations about any axis were registered with a precision of better than 0.2 ° (1 s.d.) when no translations were present. Combined rotations and translations of up to 4 ° and 15 mm were registered with 0.4 ° and 0.7 mm accuracy for each axis. The influence of setup translations on registration of rotations and vice versa was also investigated and mostly agrees with a simple geometric model. Additionally, the dependence of registration accuracy on three cost functions, angular spacing between MDRRs, pixel size, and field‐of‐view, was examined. Best results were achieved by mutual information using 0.5 ° angular spacing and a 10 × 10cm 2field‐of‐view with 140 × 140 pixels . Approximating patient motion as rigid transformation, the registration method is applied to two treatment plans and the patients’ setup errors are determined. Their magnitude was found to be ⩽ 6.1 mm and ⩽ 2.7 ° for any axis in all of the six fractions measured for each treatment plan.