Weighting functions for graph-based medical image segmentation algorithms (e.g., Graph cut) have a significant effect on the segmentation, but to our knowledge no tool provides the user with intuition towards their proper selection. The large variety, their complexity, and the limited feedback hinders comparison of choices. This paper describes a package developed to visualize the effects of various edge weighting functions and parameters, in which the image of interest is overlaid with colors depicting the relative distances from the nearest seed to each voxel. By seeing the colors vary while changing parameters, the user gains intuition into the various options for the edge weighting function. A user study demonstrating the benefits of the package is presented. It is our hope that the intuition provided by the software will result in less time required to segment medical images in the clinical work-flow.

Robot assistance can enhance minimally invasive image-guided surgery, but flexion of the thin surgical instrument shaft impairs accurate control by creating errors in the kinematic model. Two controller enhancements that can mitigate these errors are improved kinematic models that account for flexing and direct measurement of the instrument tip's position. This paper presents an experiment quantifying the benefits of these enhancements in an effort to inform development of an image-guided robot control system accurate in the presence of quasi-static instrument flexion. The study measured a controller's ability to guide a flexing instrument along user-commanded motions while preventing incursions into a forbidden region virtual fixture. Compared with the controller using neither enhancement, improved kinematics and reduced maximum incursion depth into the forbidden region by 28%, tip tracking by 67%, and both enhancements together by 83%.

Robots are useful tools in minimally invasive surgery, providing benefits such as reduction in hand tremor, navigation, and workspace scaling. Unfortunately, minimally invasive configurations result in two likely sources of kinematic error: port displacement and instrument shaft flexion. For a quasistatic system, a measure is presented that relates the errors in the robot Jacobian to the angular difference between desired motions and actual motions. Simulations and experimental data demonstrate this measure for a laboratory system. One potential use for the presented measure is, for bounded errors, determining whether the system monotonically converges for all initial and desired positions in the workspace. In addition, the measure is useful for path planning, determining less error-prone paths.

Locating arteries hidden beneath superficial tissue can be a difficult task in minimally invasive surgery. This paper reports the development of a system that finds the paths of arteries using tactile sensing. The surgeon begins by using the surgical robot to place the tactile sensor instrument on a known artery location. Signal processing algorithms locate the artery from its pulsatile pressure variation. An adaptive extrapolation algorithm then generates predicted locations for the artery based on previous measurements. After moving to the predicted location, if the artery is not located then a backtracking mechanism moves the sensor towards previously detected locations. Tests with model arteries show good tracking ability for circular arcs with curvatures as small as 80 mm, although problems with compliance in the system result in occasional loss of the artery path. Preliminary tests demonstrate the ability to transcutaneously track the radial artery in the human wrist.