Klaus W. G. Eichhorn

Path Planning for Robot-Guided Endoscopes in Deformable Environments

In this paper we present novel concepts that allow to plan time optimal paths under velocity constraints for an endoscopic robot acting in deformable environments. These environments are described by means of a simplified biomechanical model stored as a 3d volume. It permits the estimation of forces and torques caused by soft body deformations. Moreover, the parameters of the model are dynamically updated when structures are removed during an endoscopic surgery. All objectives of the path planning task are mapped to velocity constraints. In order to find an optimal path within the 5d configuration space of the endoscope, we propose a pivot point constrained global path planning in 3d employing fast marching and relax the pivot constraint afterwards for a 5d local optimization.

A model-based approach to the segmentation of nasal cavity and paranasal sinus boundaries

We present a model-driven approach to the segmentation of nasal cavity and paranasal sinus boundaries. Based on computed tomography data of a patients head, our approach aims to extract the border that separates the structures of interest from the rest of the head. This three-dimensional region information is useful in many clinical applications, e.g. diagnosis, surgical simulation, surgical planning and robot assisted surgery. The desired boundary can be made up of bone, mucosa or air what makes the segmentation process very difficult and brings traditional segmentation approaches, like e.g. region growing, to their limits. Motivated by the work of Tsai et al. [1] and Leventon et al. [2], we therefore show how a parametric level-set model can be generated from hand-segmented nasal cavity and paranasal sinus data that gives us the ability to transform the complex segmentation problem into a finited-imensional one. On this basis, we propose a processing chain for the automated segmentation of the endonasal structures that incorporates the model information and operates without any user interaction. Promising results are obtained by evaluating our approach on two-dimensional data slices of 50 patients with very diverse paranasal sinuses.

Sensorbasierte Messung mechanischer Kräfte am Endoskop während FESS

BACKGROUND To relieve the surgeon during functional endoscopic endonasal sinus surgery (FESS), the endoscope should be guided by autonomous robot assistance. The surgeon will thus have two hands free for suctioning and manipulation during FESS. PATIENTS/METHODS With a force/torque sensor mounted on the endoscope, we measured forces in six degrees of freedom in five cadaver heads and in 20 actual endoscopic sinus procedures. On the cadaver heads we performed complete endoscopic endonasal dissection of all paranasal sinuses. All forces at the endoscope were monitored continuously. RESULTS The mean forces occurring at the endoscope were 3.2 N. There were only slight differences between the in vivo and ex vivo data. We measured peak forces up to 25.2 N. In 95% of all cases, forces were lower than 7 N. CONCLUSION Forces up to 7 N are sufficient for endoscopic guidance during FESS. Peak forces are distinctive for endoscopic guidance by humans and could be optimised by sensor-based intraoperative robot guidance. Higher forces are required for surgical endoscopy of the frontal and maxillary sinuses compared with the ethmoid sinuses.

Demonstration of a prototype for robot assisted Endoscopic Sinus Surgery

In this video we show our current prototype for robot assisted endoscopy. The system requires only few and simple instructions from the surgeon, in order to guide the endoscope in an intelligent, autonomous, and safe way: The surgeon tells what to do and the robot decides how to carry out the task by choosing the best manipulation primitive in every control cycle. Several sensors are integrated into the decision process: The endoscope camera, a stereo camera system, a force/torque sensor, a biomechanical model based on CT data and statistical knowledge, a position and velocity sensor for the manipulator, and interface devices like a foot switch. The executed manipulation primitive is handled by a hybrid controller allowing to switch the control mode (e.g. trajectory following or force control) for each degree of freedom of the task frame individually.

A locally deformable statistical shape model

Statistical shape models are one of the most powerful methods in medical image segmentation problems. However, if the task is to segment complex structures, they are often too constrained to capture the full amount of anatomical variation. This is due to the fact that the number of training samples is limited in general, because generating hand-segmented reference data is a tedious and time-consuming task. To circumvent this problem, we present a Locally Deformable Statistical Shape Model that is able to segment complex structures with only a few training samples at hand. This is achieved by allowing a unique solution in each contour point. Unlike previous approaches, trying to tackle this problem by partitioning the statistical model, we do not need predefined segments. Smoothness constraints ensure that the local solution is restricted to the space of feasible shapes. Very promising results are obtained when we compare our new approach to a global fitting approach.

[Evaluation of force data with a force/torque sensor during FESS. A step towards robot-assisted surgery].

BACKGROUND To relieve the surgeon during functional endoscopic endonasal sinus surgery (FESS), the endoscope should be guided by autonomous robot assistance. The surgeon will thus have two hands free for suctioning and manipulation during FESS. PATIENTS/METHODS With a force/torque sensor mounted on the endoscope, we measured forces in six degrees of freedom in five cadaver heads and in 20 actual endoscopic sinus procedures. On the cadaver heads we performed complete endoscopic endonasal dissection of all paranasal sinuses. All forces at the endoscope were monitored continuously. RESULTS The mean forces occurring at the endoscope were 3.2 N. There were only slight differences between the in vivo and ex vivo data. We measured peak forces up to 25.2 N. In 95% of all cases, forces were lower than 7 N. CONCLUSION Forces up to 7 N are sufficient for endoscopic guidance during FESS. Peak forces are distinctive for endoscopic guidance by humans and could be optimised by sensor-based intraoperative robot guidance. Higher forces are required for surgical endoscopy of the frontal and maxillary sinuses compared with the ethmoid sinuses.

Sensorbasierte Messung mechanischer Kräfte am Endoskop während FESS@@@Evaluation of force data with a force/torque sensor during FESS: Schritte zur robotergestützten Nasennebenhöhlenchirurgie@@@A step towards robot-assisted surgery

BACKGROUND To relieve the surgeon during functional endoscopic endonasal sinus surgery (FESS), the endoscope should be guided by autonomous robot assistance. The surgeon will thus have two hands free for suctioning and manipulation during FESS. PATIENTS/METHODS With a force/torque sensor mounted on the endoscope, we measured forces in six degrees of freedom in five cadaver heads and in 20 actual endoscopic sinus procedures. On the cadaver heads we performed complete endoscopic endonasal dissection of all paranasal sinuses. All forces at the endoscope were monitored continuously. RESULTS The mean forces occurring at the endoscope were 3.2 N. There were only slight differences between the in vivo and ex vivo data. We measured peak forces up to 25.2 N. In 95% of all cases, forces were lower than 7 N. CONCLUSION Forces up to 7 N are sufficient for endoscopic guidance during FESS. Peak forces are distinctive for endoscopic guidance by humans and could be optimised by sensor-based intraoperative robot guidance. Higher forces are required for surgical endoscopy of the frontal and maxillary sinuses compared with the ethmoid sinuses.