Intraoperative 3D reconstruction of prostate brachytherapy implants with automatic pose correction

Abstract

The success of prostate brachytherapy critically depends on delivering adequate dose to the prostate gland, and the capability of intraoperatively localizing implanted seeds provides potential for dose evaluation and optimization during therapy. REDMAPS is a recently reported algorithm that carries out seed localization by detecting, matching and reconstructing seeds in only a few seconds from three acquired x-ray images (Lee et al 2011 IEEE Trans. Med. Imaging 29 38–51). In this paper, we present an automatic pose correction (APC) process that is combined with REDMAPS to allow for both more accurate seed reconstruction and the use of images with relatively large pose errors. APC uses a set of reconstructed seeds as a fiducial and corrects the image pose by minimizing the overall projection error. The seed matching and APC are iteratively computed until a stopping condition is met. Simulations and clinical studies show that APC significantly improves the reconstructions with an overall average matching rate of ⩾99.4%, reconstruction error of ⩽0.5 mm, and the matching solution optimality of ⩾99.8%.