Yusuke Kurose

Preliminary study of needle tracking in a microsurgical robotic system for automated operations

Surgical needle tracking is an important element of high-level automated operations conducted by surgical robotic systems. However, conventional needle tracking algorithms lack robust performance with different needle postures and are not applicable to the small needles used during microsurgery. This paper discusses a robust, efficient needle tracking algorithm, which is capable of estimating all of the positions and of the postures of a microsurgical needle. In the preoperative preparation stage, contour models of the microsurgical needle are generated using a 3-D CAD model and saved in a database. During the operation, the system extracts the contours of the microsurgical needle from the microscopic image using the edge and the color information. The system then calculates the likelihood of the contour models in the database by matching the contours extracted from the microscopic image. The experimental results indicated that our proposed method has high accuracy when tracking a microsurgical needle, and that it performed robustly with different needle postures.

Feedback methods for collision avoidance using virtual fixtures for robotic neurosurgery in deep and narrow spaces

Robotic assistance enables a surgeon to perform dexterous and precise manipulations. However, conducting robot assisted neurosurgery within the deep and narrow spaces of the brain presents the risk of unexpected collisions between the shafts of robotic instruments and their surroundings out of the microscopic view. Thus, we propose the provision of feedback using a truncated cone shaped virtual fixture generated by marking the edges of the top and bottom plane of a workspace in the deep and narrow spaces within the brain with the slave manipulator. The experimental results show that the virtual fixture generation method could precisely model the workspace. We also implemented force feedback, visual feedback, and motion scaling feedback in the microsurgical robotic system in order to inform the surgeon of the risk of collision. Performance of each feedback method and their combinations was evaluated in two experiments. The experimental results showed that the combination of the force and the visual feedback methods were the most beneficial for avoiding collisions.

Towards robust needle segmentation and tracking in pediatric endoscopic surgery.

Neonatal tracheoesophageal fistula surgery poses technical challenges to surgeons, given the limited workspace and fragile tissues. In previous studies from our collaborators, a neonatal chest model was developed to allow surgeons to enhance their performance, such as suturing ability, before conducting actual surgery. Endoscopic images are recorded while the model is used, and surgeon skill can be manually assessed by using a 29-point checklist. However, that is a time-consuming process. In the checklist, there are 15 points that regard needle position and angle that could be automatized if the needle could be efficiently tracked. This paper is a first step towards the goal of tracking the needle. Pixel HSV color space channels, opponent color space channels, and pixel oriented gradient information are used as features to train a random forest model. Three methods are compared in the segmentation stage: single pixel features, pixel and its immediate 10-by-10 square window features, and the features of randomly offset pixels in a larger 169-by-169 window. Our analysis using 9-fold cross-validation shows that using randomly offset pixels increases needle segmentation f-measure by 385 times when comparing with single pixel color, and by 3 times when comparing with the immediate square window even though the same amount of memory is used. The output in the segmentation step is fed into a particle filter to track the full state of the needle.

On the use of general-purpose serial-link manipulators in eye surgery

Vitreo-retinal surgery is known to be very challenging because of the minuscule structures of the retina, which are smaller than the hand tremor amplitude of ∼100 μm. In this work, the use of a serial-link general-purpose manipulator in eye surgery to increase the accuracy was assessed. The proposed system showed a 3-sigma accuracy of 22 ± 36 μm when tracing a 1 mm square with an ophthalmic micropipette. The 3-sigma remote center of motion error was 0.14±0.23 mm when tracing a 7 mm square.

Intelligent control of neurosurgical robot MM-3 using dynamic motion scaling

OBJECTIVE Advanced and intelligent robotic control is necessary for neurosurgical robots, which require great accuracy and precision. In this article, the authors propose methods for dynamically and automatically controlling the motion-scaling ratio of a master-slave neurosurgical robotic system to reduce the task completion time. METHODS Three dynamic motion-scaling modes were proposed and compared with the conventional fixed motion-scaling mode. These 3 modes were defined as follows: 1) the distance between a target point and the tip of the slave manipulator, 2) the distance between the tips of the slave manipulators, and 3) the velocity of the master manipulator. Five test subjects, 2 of whom were neurosurgeons, sutured 0.3-mm artificial blood vessels using the MM-3 neurosurgical robot in each mode. RESULTS The task time, total path length, and helpfulness score were evaluated. Although no statistically significant differences were observed, the mode using the distance between the tips of the slave manipulators improves the suturing performance. CONCLUSIONS Dynamic motion scaling has great potential for the intelligent and accurate control of neurosurgical robots.