Hough Space Parametrization: Ensuring Global Consistency in Intensity-Based Registration
Intensity based registration is a challenge when images to be registered have insufficient amount of information in their overlapping region. Especially, in the absence of dominant structures such as strong edges in this region, obtaining a solution that satisfies global structural consistency becomes difficult. In this work, we propose to exploit the vast amount of available information beyond the overlapping region to support the registration process. To this end, a novel global regularization term using Generalized Hough Transform is designed that ensures the global consistency when the local information in the overlap region is insufficient to drive the registration. Using prior data, we learn a parametrization of the target anatomy in Hough space. This parametrization is then used as a regularization for registering the observed partial images without using any prior data. Experiments on synthetic as well as on sample real medical images demonstrate the good performance and potential use of the proposed concept.
KeywordsPrior Data Partial Image Global Regularization Target Registration Error Rigid Registration
- 2.Gall, J., Lempitsky, V.: Class-specific hough forests for object detection. In: Decision Forests for Computer Vision and Medical Image Analysis, pp. 143–157. Springer (2013)Google Scholar
- 4.Johnson, S.G.: The nlopt nonlinear-optimization package, http://ab-initio.mit.edu/wiki/index.php/NLopt (accessed February 21, 2014)
- 6.Leibe, B., Leonardis, A., Schiele, B.: Combined object categorization and segmentation with an implicit shape model. In: Workshop on Statistical Learning in Computer Vision (ECCV) (May 2004)Google Scholar
- 10.Shams, R., Barnes, N., Hartley, R.: Image registration in hough space using gradient of images. In: 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications, pp. 226–232. IEEE (2007)Google Scholar
- 12.Varnavas, A., Carrell, T., Penney, G.: Fully automated initialisation of 2D-3D image registration. In: 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI), pp. 568–571. IEEE (2013)Google Scholar