Automated Linear and Non-Linear Path Planning for Neurosurgical Interventions

Peikert S, Kunz C, Fischer N, Hlavac M, Pala A, Schneider M, Mathis-Ullrich F (2022)

Publication Type: Conference contribution

Publication year: 2022

Journal

Proceedings - IEEE International Conference on Robotics and Automation Institute of Electrical and Electronics Engineers

Publisher: Institute of Electrical and Electronics Engineers Inc.

Pages Range: 7731-7737

Conference Proceedings Title: Proceedings - IEEE International Conference on Robotics and Automation

Event location: Philadelphia, PA US

ISBN: 9781728196817

DOI: 10.1109/ICRA46639.2022.9811679

Abstract

Recent advances in medical technology have produced a number of flexible instruments that are capable of traversing non-linear paths. This is of special interest in the field of neurosurgery. However, the non-rigid instruments have the disadvantage that path planning becomes increasingly difficult. In addition to anatomical risk factors, the mechanical properties and constraints of the specific instrument must also be considered. To support surgeons to deal with the increase in planning complexity, we present a novel method for both linear and arbitrary follow-the-leader flexible path planning. Our method is utilizing patient-specific image data, which is then used to generate a multi-objective problem consisting of conventional risk metrics for path planning in high-risk regions like the accumulated path cost or the distance to risk structures. Simultaneously, the path-problem is also constraint to mechanical properties of the instrument such as curvature or maximum operational length. Optimal paths can then be generated by solving a multi-objective problem by approximating the Pareto front. We show that our method can automatically generate linear and non-linear paths for neurosurgical interventions in the human brain in less than 2 minutes. Furthermore, we show that the proposed automated method generates paths with 87% reduced risk compared to standard of care plannings.

Authors with CRIS profile

Steffen Peikert
Franziska Mathis-Ullrich

Involved external institutions

Universitätsklinikum Ulm DE Germany (DE) Karlsruhe Institute of Technology (KIT) DE Germany (DE)

How to cite

APA:

Peikert, S., Kunz, C., Fischer, N., Hlavac, M., Pala, A., Schneider, M., & Mathis-Ullrich, F. (2022). Automated Linear and Non-Linear Path Planning for Neurosurgical Interventions. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 7731-7737). Philadelphia, PA, US: Institute of Electrical and Electronics Engineers Inc..

MLA:

Peikert, Steffen, et al. "Automated Linear and Non-Linear Path Planning for Neurosurgical Interventions." Proceedings of the 39th IEEE International Conference on Robotics and Automation, ICRA 2022, Philadelphia, PA Institute of Electrical and Electronics Engineers Inc., 2022. 7731-7737.

BibTeX: Download