Internal evaluation of registration results for radiographic images
This work focuses on internal gray level based evaluation of image registration results. The motivation is to provide an approach for self-diagnosis in the scope of a patient alignment system based on rigid registration of real and reconstructed X-ray images. As an automatic system should provide expressive indicators for the correctness of the outcome, we propose a method to estimate the probability for the resulting transformations to lie within a predefined window of acceptable values. Based purely on image gray values, the approach is independent from previous knowledge about the image. By registration of corresponding fragments of both images we generate redundancy and define the probability density of the resulting transformations. The proposed method is tested comparing digital reconstucted radiographs (DRRs) to X-ray images. By introducing geometric and radiometric deviations we show that a reliable self-diagnosis is possible.