Speaker
Description
Concentric tube continuum robots (CTCRs) allow to consider minimally invasive deep brain surgeries which could not be realized with straight cannulas and manual surgery planning, as it is state of the art. We present a design assistant for finding personalized tube configurations (e.g. thicknesses and precurvatures of the nested cannulae) for the CTCR and an automated path planning. The core of the design assistant is the modelling of a high-dimensional nonlinear constrained optimization problem. It is derived from the brain topology obtained from labeling MRI scans, further medical constraints and objectives, such as minimally invasive interventions (i.e. shortest tube lengths or minimal penetrations), as well as mechanical constraints on the cannulae design, e.g. given by material parameters, and a cannulae model. The optimization problem is then solved by gradient-based solution methods in combination with evolutionary algorithms, such that an optimal design together with the optimal surgery plan is returned.
