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2019 | OriginalPaper | Buchkapitel

Generalized Non-rigid Point Set Registration with Hybrid Mixture Models Considering Anisotropic Positional Uncertainties

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Abstract

Image-to-patient or pre-operative to intra-operative registration is an essential problem in computer-assisted surgery (CAS). Non-rigid or deformable registration is still a challenging problem with partial overlapping between point sets due to limited camera view, missing data due to tumor resection and the surface reconstruction error intra-operatively. In this paper, we propose and validate a normal-vector assisted non-rigid registration framework for accurately registering soft tissues in CAS. Two stages including rigid and non-rigid registrations are involved in the framework. In the stage of the rigid registration that does the initial alignment, the normal vectors extracted from the point sets are used while the position uncertainty is assumed to be anisotropic. With the normal vectors incorporated, the algorithm can better recover the point correspondences and is more robust to intra-operative partial data which is often the case in a typical laparoscopic surgery. In the stage of the non-rigid registration, the anisotropic coherent point drift (CPD) method is formulated, where the isotropic error assumption is generalized to anisotropic cases. Extensive experiments on the human liver data demonstrate our proposed algorithm’s several great advantages over the existing state-of-the-art ones. First, the rigid transformation matrix is recovered more accurately. Second, the proposed registration framework is much more robust to partial scan. Besides, the anisotropic CPD outperforms the original CPD significantly in terms of robustness to noise.

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\(\theta _{deg}=\text {arccos}\Big [ \frac{ \text {tr}(\mathbf {R}^g \mathbf {R}^{\mathsf {T}} ) -1}{2}\Big ]/\pi \times 180\), where \(\mathbf {R}^g\) and \(\mathbf {R}\) denote the ground-truth and the computed rotation matrix using one specific test method, respectively.
 
Literatur
2.
Zurück zum Zitat Cignoni, P., Callieri, M., Corsini, M., Dellepiane, M., Ganovelli, F., Ranzuglia, G.: MeshLAB: an open-source mesh processing tool. In: Eurographics Italian Chapter Conference, pp. 129–136 (2008) Cignoni, P., Callieri, M., Corsini, M., Dellepiane, M., Ganovelli, F., Ranzuglia, G.: MeshLAB: an open-source mesh processing tool. In: Eurographics Italian Chapter Conference, pp. 129–136 (2008)
3.
Zurück zum Zitat Collins, J.A., et al.: Improving registration robustness for image-guided liver surgery in a novel human-to-phantom data framework. IEEE TMI 36(7), 1502–1510 (2017) Collins, J.A., et al.: Improving registration robustness for image-guided liver surgery in a novel human-to-phantom data framework. IEEE TMI 36(7), 1502–1510 (2017)
4.
Zurück zum Zitat Luo, J., et al.: Using the variogram for vector outlier screening: application to feature-based image registration. IJCARS 13(12), 1871–1880 (2018) Luo, J., et al.: Using the variogram for vector outlier screening: application to feature-based image registration. IJCARS 13(12), 1871–1880 (2018)
7.
Zurück zum Zitat Min, Z., Wang, J., Meng, M.Q.H.: Robust generalized point cloud registration using hybrid mixture model. In: ICRA 2018, pp. 4812–4818. IEEE (2018) Min, Z., Wang, J., Meng, M.Q.H.: Robust generalized point cloud registration using hybrid mixture model. In: ICRA 2018, pp. 4812–4818. IEEE (2018)
10.
Zurück zum Zitat Min, Z., Wang, J., Song, S., Meng, M.Q.H.: Robust generalized point cloud registration with expectation maximization considering anisotropic positional uncertainties. In: IROS 2018, pp. 1290–1297. IEEE (2018) Min, Z., Wang, J., Song, S., Meng, M.Q.H.: Robust generalized point cloud registration with expectation maximization considering anisotropic positional uncertainties. In: IROS 2018, pp. 1290–1297. IEEE (2018)
11.
Zurück zum Zitat Myronenko, A., Song, X.: Point set registration: coherent point drift. IEEE Trans. Pattern Anal. Mach. Intell. 32(12), 2262–2275 (2010)CrossRef Myronenko, A., Song, X.: Point set registration: coherent point drift. IEEE Trans. Pattern Anal. Mach. Intell. 32(12), 2262–2275 (2010)CrossRef
12.
Zurück zum Zitat Ravikumar, N., Gooya, A., Beltrachini, L., Frangi, A.F., Taylor, Z.A.: Generalised coherent point drift for group-wise multi-dimensional analysis of diffusion brain MRI data. Med. Image Anal. 53, 47–63 (2019)CrossRef Ravikumar, N., Gooya, A., Beltrachini, L., Frangi, A.F., Taylor, Z.A.: Generalised coherent point drift for group-wise multi-dimensional analysis of diffusion brain MRI data. Med. Image Anal. 53, 47–63 (2019)CrossRef
13.
Zurück zum Zitat Ravikumar, N., Gooya, A., Frangi, A.F., Taylor, Z.A.: Generalised coherent point drift for group-wise registration of multi-dimensional point sets. In: Descoteaux, M., Maier-Hein, L., Franz, A., Jannin, P., Collins, D.L., Duchesne, S. (eds.) MICCAI 2017. LNCS, vol. 10433, pp. 309–316. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-66182-7_36CrossRef Ravikumar, N., Gooya, A., Frangi, A.F., Taylor, Z.A.: Generalised coherent point drift for group-wise registration of multi-dimensional point sets. In: Descoteaux, M., Maier-Hein, L., Franz, A., Jannin, P., Collins, D.L., Duchesne, S. (eds.) MICCAI 2017. LNCS, vol. 10433, pp. 309–316. Springer, Cham (2017). https://​doi.​org/​10.​1007/​978-3-319-66182-7_​36CrossRef
14.
Zurück zum Zitat Robu, M.R., et al.: Global rigid registration of ct to video in laparoscopic liver surgery. Int. J. Comput. Assist. Radiol. Surg. 13(6), 947–956 (2018)CrossRef Robu, M.R., et al.: Global rigid registration of ct to video in laparoscopic liver surgery. Int. J. Comput. Assist. Radiol. Surg. 13(6), 947–956 (2018)CrossRef
15.
Zurück zum Zitat Sinha, A., Liu, X., Reiter, A., Ishii, M., Hager, G.D., Taylor, R.H.: Endoscopic navigation in the absence of CT imaging. In: Frangi, A.F., Schnabel, J.A., Davatzikos, C., Alberola-López, C., Fichtinger, G. (eds.) MICCAI 2018. LNCS, vol. 11073, pp. 64–71. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00937-3_8CrossRef Sinha, A., Liu, X., Reiter, A., Ishii, M., Hager, G.D., Taylor, R.H.: Endoscopic navigation in the absence of CT imaging. In: Frangi, A.F., Schnabel, J.A., Davatzikos, C., Alberola-López, C., Fichtinger, G. (eds.) MICCAI 2018. LNCS, vol. 11073, pp. 64–71. Springer, Cham (2018). https://​doi.​org/​10.​1007/​978-3-030-00937-3_​8CrossRef
16.
Zurück zum Zitat Suwelack, S., et al.: Physics-based shape matching for intraoperative image guidance. Med. Phys. 41(11), 111901 (2014)CrossRef Suwelack, S., et al.: Physics-based shape matching for intraoperative image guidance. Med. Phys. 41(11), 111901 (2014)CrossRef
Metadaten
Titel
Generalized Non-rigid Point Set Registration with Hybrid Mixture Models Considering Anisotropic Positional Uncertainties
verfasst von
Zhe Min
Li Liu
Max Q.-H. Meng
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-32254-0_61