We develop a new motion planning algorithm for a variant of a Dubins car with binary left/right steering and apply it to steerable needles, a new class of flexible bevel-tip medical needles that physicians can steer through soft tissue to reach clinical targets inaccessible to traditional stiff needles. Our method explicitly considers uncertainty in needle motion due to patient differences and ...

PURPOSE Positron emission tomography (PET) provides physiologic information that is not available from computed tomography (CT) or magnetic resonance studies. PET images may allow more accurate delineation of three-dimensional treatment planning target volumes of brachytherapy gynecologic (GYN) implants. This study evaluates the feasibility of using PET as the sole source of target, normal stru...

The real-world application of planning techniques often requires models with numeric fluents. However, these fluents are not directly supported by most planners and heuristics. We describe a family of planning algorithms that takes a numeric planning problem and produces an abstracted representation that can be solved using any classical planner. The resulting abstract plan is generalized into ...

Cover FigureAlthough both the PRR and area 5d have been found to be intimately involved in visually guided reach, several recent studies of reference frame, decision making, and sequential movement suggest that they might play distinct roles in planning and control of reach at different levels of complexity, indicating a hierarchical circuitry participating in translation from abstract intentio...

The goal of dental implant therapy is the accurate and predictable restoration of a patient’s dentition. These goals are best achieved when all members of the surgical and restorative team are working together on diagnosis, planning, and reconstruction. The recent introduction of new 3dimensional (3D) diagnostic and treatment planning technologies in implant dentistry have created an environmen...

Monte Carlo tree search (MCTS) is a sampling and simulation based technique for searching in large search spaces containing both decision nodes and probabilistic events. This technique has recently become popular due to its successful application to games, e.g. Poker Van den Broeck et al. (2009) and Go Coulom (2006); Chaslot et al. (2006); Gelly and Silver (2012)). Such games have known rules a...

We present a method for exploiting the symmetry in the planning graph structure and certain redundancies inherent in the Graphplan algorithm, so as to improve its backward search. The main insight underlying our method is that due to these features the backward search conducted at level k + 1 of the graph is essentially a replay of the search conducted at the previous level k with certain well-...

A computer algorithm for determining optimal surgical paths in the brain is presented. The algorithm computes a cost function associated with each point on the outer brain boundary, which is treated as a candidate entry point. The cost function is determined partly based on a segmentation of the patients images into gray and white matter, and partly based on a spatially transformed atlas of the...

The great variety of users of the services available on the internet raised the problem of finding flexible forms of presentation and interaction, which depend on the specific user's characteristics and needs. In this article we present an approach to adaptation, which exploits the reasoning capabilities of a rational agent. The key idea, which makes this approach orthogonal to personalization ...

Classical planning is the problem of finding a sequence of actions for achieving a goal from an initial state assuming that actions have deterministic effects. The most effective approach for finding such plans is based on heuristic search guided by heuristics extracted automatically from the problem representation. In this thesis, we introduce alternative approaches for performing inference ov...