220 likes | 330 Views
Feedback Control for Steering Needles Through 3D Deformable Tissue Using Helical Paths. Kris Hauser, Ron Alterovitz , Nuttapon Chentanez , Allison Okamura, Ken Goldberg. Yajia Zhang. Background. Needles are used in medicine for a wide range of diagnostic and therapy delivery procedures.
E N D
Feedback Control for Steering Needles Through 3D Deformable Tissue Using Helical Paths Kris Hauser, Ron Alterovitz, NuttaponChentanez, Allison Okamura, Ken Goldberg. Yajia Zhang
Background • Needles are used in medicine for a wide range of diagnostic and therapy delivery procedures. • Needle tip must be positioned accurately at the target in the tissue.But the process requires skills. Errors may occur even under image guidance. • Feedback controller that steers the needle and places the needle tip at the target even under the perturbation of the tissue and deflection of the needle trajectory.
Background • Bevel-tip steerable needle • Steering the needle: • Force along the z axis. Cause the needle tip rotate about the x axis. • Rotate about the z axis. • Constant-Insertion-Speed and Constant-Twist-Rate Helix Trajectory of needle tip • Needle tip position determined by inserted distance d and twist rate φ.
Goal • Feedback controller to steer the bevel-tip needle with: 1.Constant insertion speed 2.Different twist rate to reach the target in the tissue.
Why real time planner • Deformation of the tissue. • Cause position of the target change. • Deflection of the planned trajectory.
Controller Framework • For every iteration: • Propose: Generate a set P of proposal trajectories. Different φmaps to different trajectory. • Select: Find the trajectory with control φ(d)in the set P that achieves the minimal distance to the target. • Execute: Insert according to φ(d) and constant velocity for time Δt.
I. ProposeGenerate Proposal Trajectories • When inserting the needle into the tissue, we build the coordinate frame according to the position of the needle tip.
Constant-Twist-Rate Helical Paths • After moving along the helix trajectory, we need to know what the coordinate of the need tip according to the initial frame. • :Helix with radius a, slope θ and oriented along the z axis.
Constant-Twist-Rate Helical Paths • : coordinate of the needle tip followed under a constant twist rate φand insertion d. • Rigid Transformation:
Constant-Twist-Rate Reachable Set • The trajectory with infinity twist rate will almost along the z axis.
Alternating-Twist Maneuver • For finite maximum twist rate, alternating-twist maneuver can reduce the gap along the z axis.
Alternating-Twist Maneuver • To fill in the gap, we consider the maneuver that makes a full turn of the helix with twist rate , and another with twist rate
II. SelectChoose the trajectory with minimum distance to target • Minimize • + proposal trajectories in the gap • Auxiliary function is used to calculate a tight lower bound of given a region R.
Branch-and-Bound • A search tree recursively split the space into subregions. We maintain the helix * and insertion distance d* which give the minimum value of f. If of subregion R gives value larger than f, we can safely prune the region. We continue the process until f achieves an ε tolerance.
III. Execute • Insert according to the select trajectory for time Δt or some distance Δd.
Simulation Result • Accuracy: The final distance from the needle tip to the target when the controller terminates. • Reference controller: A refresh occurs every 2%r of insertion distance, maximum twist rate = 10πrad/r
Simulation Result • Accuracy Without Perturbations:
Simulation Result • Accuracy Under Perturbations and Modeling Errors: • Gaussian Noise
Possible Improvement • Avoid the obstacles Set intermediate Target’. When reaching Target’, we may just assume the Target moved. Target Target’
Issue About Real Time Planning • How often should we re-plan? • The reference controller refreshes after inserting length s= 2%r to achieve high accuracy. • What if the deformation and deflection do not happen (or some tiny changes)? • Complex system may require intense computation in re-planning.