Comparative analysis of non-rigid registration techniques for liver surface registration

Bipasha Kundu; Zixin Yang; Richard Simon; Cristian Linte

doi:10.1117/12.3008594

29 March 2024 Comparative analysis of non-rigid registration techniques for liver surface registration

Bipasha Kundu, Zixin Yang, Richard Simon, Cristian Linte

Proceedings Volume 12928, Medical Imaging 2024: Image-Guided Procedures, Robotic Interventions, and Modeling; 129282B (2024) https://doi.org/10.1117/12.3008594
Event: SPIE Medical Imaging, 2024, San Diego, California, United States

Conference Poster

Abstract

Non-rigid surface-based soft tissue registration is crucial for surgical navigation systems, but its adoption still faces several challenges due to the large number of degrees of freedom and the continuously varying and complex surface structures present in the intra-operative data. By employing non-rigid registration, surgeons can integrate the pre-operative images into the intra-operative guidance environment, providing real-time visualization of the patient’s complex pre- and intra-operative anatomy in a common coordinate system to improve navigation accuracy. However, many of the existing registration methods, including those for liver applications, are inaccessible to the broader community. To address this limitation, we present a comparative analysis of several open-source, non-rigid surface-based liver registration algorithms, with the overall goal of contrasting their strength and weaknesses and identifying an optimal solution. We compared the robustness of three optimization-based and one data-driven nonrigid registration algorithms in response to a reduced visibility ratio (reduced partial views of the surface) and to an increasing deformation level (mean displacement), reported as the root mean square error (RMSE) between the pre-and intra-operative liver surface meshed following registration. Our results indicate that the Gaussian Mixture Model - Finite Element Model (GMM-FEM) method consistently yields a lower post-registration error than the other three tested methods in the presence of both reduced visibility ratio and increased intra-operative surface displacement, therefore offering a potentially promising solution for pre- to intra-operative nonrigid liver surface registration.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Bipasha Kundu, Zixin Yang, Richard Simon, and Cristian Linte "Comparative analysis of non-rigid registration techniques for liver surface registration", Proc. SPIE 12928, Medical Imaging 2024: Image-Guided Procedures, Robotic Interventions, and Modeling, 129282B (29 March 2024); https://doi.org/10.1117/12.3008594

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