Bidirectional Generalised Rigid Point Set Registration

Ang Zhang1; Zhe Min2; Li Liu1; Max Q.-H. Meng3

10.1109/ICRA48891.2023.10160361

2023-05-29

IEEE International Conference on Robotics and Automation (ICRA)

1050-4729

2577-087X

979-8-3503-2366-5

2023 IEEE International Conference on Robotics and Automation (ICRA)

2023-May

6873-6879

29 May-2 June 2023

London, United Kingdom

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

In medical robotics and image-guided surgery (IGS), registration is needed in order to align together the coordinate frames of robots, medical imaging modalities, surgical tools, and patients. Existing registration algorithms often assume one point set to be a noise-free model while the other to contain noise and outliers. However, in real scenarios, noise and outliers can exist in both point sets to be registered. To eliminate the above-mentioned challenge, in this paper, we formally formulate the Bi-directional Generalised Rigid Point Set Registration (Bi-GRPSR) problem where normal vectors are adopted, bi-directional probability density function (PDFs) and Hybrid Mixture Models (HMMs) are constructed to derive the objective function. Bi-GRPSR considering anisotropic positional noise is thus cast as a maximum likelihood estimation (MLE) problem, which is solved by the proposed Bi-directional Generalised Anisotropic Coherent Point Drift (Bi-AGCPD) where spatially nearby points are considered to move coherently and iterative expectation maximization (EM) steps are involved. Experimental results on two human bone point sets, under different settings of noise, outliers, and overlapping ratios, validate the effectiveness and improvements of Bi-AGCPD over existing probabilistic and learning-based methods.

Learning systems Maximum likelihood estimation Uncertainty Robot kinematics Surgery Hidden Markov models Bidirectional control

其他

英语

EI ; CPCI-S

National Key R&D program of China[2019YFB1312400]

Automation & Control Systems ; Computer Science ; Engineering ; Robotics

Automation & Control Systems ; Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Robotics

WOS:001036713005046

20233514632673

Anisotropy ; Geometry ; Iterative methods ; Maximum principle ; Medical imaging ; Probability density function ; Robotic surgery ; Statistics ; Surgical equipment

Biomedical Engineering:461.1 ; Medicine and Pharmacology:461.6 ; Biomedical Equipment, General:462.1 ; Robot Applications:731.6 ; Imaging Techniques:746 ; Mathematics:921 ; Numerical Methods:921.6 ; Statistical Methods:922 ; Probability Theory:922.1 ; Mathematical Statistics:922.2 ; Physical Properties of Gases, Liquids and Solids:931.2

IEEE

1.Department of Electronic Engineering, The Chinese University of Hong Kong, N.T., Hong Kong SAR, China
2.School of Control Science and Engineering, Shandong University, China
3.Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China

Ang Zhang,Zhe Min,Li Liu,et al. Bidirectional Generalised Rigid Point Set Registration[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2023:6873-6879.