An accurate algorithm to match imperfectly matched images for XXXX detection without markers.

@entity5 @entity2
UNASSIGNED: In order to locate @entity2 on kV projection images without internal markers, digitally reconstructed radiographs (DRRs) are created and compared with projection images. However, @entity2 always move due to respiration and their locations change on projection images while they are static on DRRs. In addition, global image intensity discrepancies exist between DRRs and projections due to their different image orientations, scattering, and noises. This adversely affects comparison accuracy. A simple but efficient comparison algorithm is reported to match imperfectly matched projection images and DRRs. The kV projection images were matched with different DRRs in two steps. Preprocessing was performed in advance to generate two sets of DRRs. The @entity5 were removed from the planning 3D CT for a single phase of planning 4D CT images using planning contours of @entity5 . DRRs of background and DRRs of @entity5 were generated separately for every projection angle. The first step was to match projection images with DRRs of background signals. This method divided global images into a matrix of small tiles and similarities were evaluated by calculating normalized cross-correlation (NCC) between corresponding tiles on projections and DRRs. The tile configuration (tile locations) was automatically optimized to keep the @entity5 within a single projection tile that had a bad matching with the corresponding DRR tile. A pixel-based linear transformation was determined by linear interpolations of tile transformation results obtained during tile matching. The background DRRs were transformed to the projection image level and subtracted from it. The resulting subtracted image now contained only the @entity5 . The second step was to register DRRs of @entity5 to the subtracted image to locate the @entity5 . This method was successfully applied to kV fluoro images (about 1000 images) acquired on a Vero (BrainLAB) for @entity5 tracking on phantom studies. Radiation opaque markers were implanted and used as ground truth for @entity5 positions. Although other organs and bony structures introduced strong signals superimposed on @entity5 at some angles, this method accurately located @entity5 on every projection over 12 gantry angles. The maximum error was less than 2.2 mm, while the total average error was less than 0.9mm. This algorithm was capable of detecting @entity5 without markers, despite strong background signals.
