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2D/3D registration algorithm for lung brachytherapy
Author(s) -
Zvonarev P. S.,
Farrell T. J.,
Hunter R.,
Wierzbicki M.,
Hayward J. E.,
Sur R. K.
Publication year - 2013
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 - 10.1118/1.4788663
Subject(s) - image registration , voxel , brachytherapy , mutual information , computer science , computer vision , imaging phantom , artificial intelligence , similarity measure , medical imaging , similarity (geometry) , algorithm , nuclear medicine , medicine , image (mathematics) , radiology , radiation therapy
Purpose: A 2D/3D registration algorithm is proposed for registering orthogonal x‐ray images with a diagnostic CT volume for high dose rate (HDR) lung brachytherapy.Methods: The algorithm utilizes a rigid registration model based on a pixel/voxel intensity matching approach. To achieve accurate registration, a robust similarity measure combining normalized mutual information, image gradient, and intensity difference was developed. The algorithm was validated using a simple body and anthropomorphic phantoms. Transfer catheters were placed inside the phantoms to simulate the unique image features observed during treatment. The algorithm sensitivity to various degrees of initial misregistration and to the presence of foreign objects, such as ECG leads, was evaluated.Results: The mean registration error was 2.2 and 1.9 mm for the simple body and anthropomorphic phantoms, respectively. The error was comparable to the interoperator catheter digitization error of 1.6 mm. Preliminary analysis of data acquired from four patients indicated a mean registration error of 4.2 mm.Conclusions: Results obtained using the proposed algorithm are clinically acceptable especially considering the complications normally encountered when imaging during lung HDR brachytherapy.