Registration with Adjacent Anatomical Structures for Cardiac Resynchronization Therapy Guidance
The clinical applications and benefits of multi-modal image registration are wide-ranging and well established. Current image based approaches exploit cross-modality information, such as landmarks or anatomical structures, which is visible in both modalities. A lack of cross-modality information can prohibit accurate automatic registration. This paper proposes a novel approach for MR to X-ray image registration which uses prior knowledge of adjacent anatomical structures to enable registration without cross-modality image information. The registration of adjacent structures formulated as a partial surface registration problem which is solved using a globally optimal ICP method. The practical clinical application of the approach is demonstrated on an image guided cardiac resynchronization therapy procedure. The left ventricle (segmented from pre-operative MR) is registered to the coronary vessel tree (extracted from intra-operative fluoroscopic images). The proposed approach is validated on synthetic and phantom data, where the results show a good comparison with the ground truth registrations. The vertex-to-vertex MAE was \(3.28\pm 1.18\) mm for 10 X-ray image pairs of the phantom.
- 3.Truong, M.V.N., Aslam, A., Rinaldi, C.A., Razavi, R., Penney, G.P., Rhode, K.: Preliminary investigation: 2D–3D registration of MR and X-ray cardiac images using catheter constraints. In: MICCAI Workshop on Cardiovascular Interventional Imaging and Biophysical Modelling, London, pp. 1–9 (2009)Google Scholar
- 4.Bourier, F., Brost, A., Yatziv, L., Hornegger, J., Strobel, N., Kurzidim, K.: Coronary sinus extraction for multimodality registration to guide transseptal puncture. In: 8th Interventional MRI Symposium, Leipzig, pp. 311–313 (2010)Google Scholar
- 5.Faber, T.L., Santana, C.A., Garcia, E.V., Candell-Riera, J., Folks, R.D., Peifer, J.W., Hopper, A., Aguade, S., Angel, J., Klein, J.L.: Three-dimensional fusion of coronary arteries with myocardial perfusion distributions: clinical validation. J. Nuclear Med. 45(5), 745–753 (2004)Google Scholar
- 6.Jolly, M.-P., Guetter, C., Lu, X., Xue, H., Guehring, J.: Automatic segmentation of the myocardium in cine MR images using deformable registration. In: Camara, O., Konukoglu, E., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds.) STACOM 2011. LNCS, vol. 7085, pp. 98–108. Springer, Heidelberg (2012). doi:10.1007/978-3-642-28326-0_10 CrossRefGoogle Scholar
- 9.Yang, J., Li, H., Jia, Y.: Go-ICP: solving 3D registration efficiently and globally optimally. In: 2013 IEEE International Conference on Computer Vision, pp. 1457–1464 (2013)Google Scholar
- 10.Yang, J., Li, H., Campbell, D., Jia, Y.: Go-ICP: a globally optimal solution to 3D ICP point-set registration. IEEE Trans. Pattern Anal. Mach. Intell. PP(99), 1–14 (2015)Google Scholar