Automated matching of corresponding seed images of three simulator radiographs to allow 3D triangulation of implanted seeds

Abstract

To match corresponding seed images in different radiographs so that the 3D seed locations can be triangulated automatically and without ambiguity requires (at least) three radiographs taken from different perspectives, and an algorithm that finds the proper permutations of the seed-image indices. Matching corresponding images in only two radiographs introduces inherent ambiguities which can be resolved only with the use of non-positional information obtained with intensive human effort. Matching images in three or more radiographs is an 'NP (Non-determinant in Polynomial time)-complete' problem. Although the matching problem is fundamental, current methods for three-radiograph seed-image matching use 'local' (seed-by-seed) methods that may lead to incorrect matchings. We describe a permutation-sampling method which not only gives good 'global' (full permutation) matches for the NP-complete three-radiograph seed-matching problem, but also determines the reliability of the radiographic data themselves, namely, whether the patient moved in the interval between radiographic perspectives.