Three‐dimensional tomosynthetic image restoration for brachytherapy source localization

Abstract

Tomosynthetic image reconstruction allows for the production of a virtually infinite number of slices from a finite number of projection views of a subject. If the reconstructed image volume is viewed in toto, and the three‐dimensional (3D) impulse response is accurately known, then it is possible to solve the inverse problem (deconvolution) using canonical image restoration methods (such as Wiener filtering or solution by conjugate gradient least squares iteration) by extension to three dimensions in either the spatial or the frequency domains. This dissertation presents modified direct and iterative restoration methods for solving the inverse tomosynthetic imaging problem in 3D. The significant blur artifact that is common to tomosynthetic reconstructions is deconvolved by solving for the entire 3D image at once. The 3D impulse response is computed analytically using a fiducial reference schema as realized in a robust, self‐calibrating solution to generalized tomosynthesis. 3D modulation transfer function analysis is used to characterize the tomosynthetic resolution of the 3D reconstructions. The relevant clinical application of these methods is 3D imaging for brachytherapy source localization. Conventional localization schemes for brachytherapy implants using orthogonal or stereoscopic projection radiographs suffer from scaling distortions and poor visibility of implanted seeds, resulting in compromised source tracking (reported errors: 2–4 mm) and dosimetric inaccuracy. 3D image reconstruction (using a well‐chosen projection sampling scheme) and restoration of a prostate brachytherapy phantom is used for testing. The approaches presented in this work localize source centroids with submillimeter error in two Cartesian dimensions and just over one millimeter error in the third.