Many technologies currently exist that are capable of analyzing the surface of solid samples under ambient or vacuum conditions, but they are typically limited to smooth, planar surfaces. Those few that can be applied to nonplanar surfaces, however, require manual sampling and a high degree of human intervention. Herein, we describe a new platform, Robotic Surface Analysis Mass Spectrometry (RoSA-MS), for direct surface sampling of three-dimensional (3D) objects. In RoSA-MS, a sampling probe is attached to a robotic arm that has 360° rotation through 6 individual joints. A 3D laser scanner, also attached to the robotic arm, generates a digital map of the sample surface that is used to direct a probe to specific ( x, y, z) locations. The sampling probe consists of a spring-loaded needle that briefly contacts the object surface, collecting trace amounts of material. The probe is then directed at an open port liquid sampling interface coupled to the electrospray ion source of a mass spectrometer. Material on the probe tip is dissolved by the solvent flow in the liquid interface and mass analyzed with high mass resolution and accuracy. The surface of bulky, nonplanar objects can thus be probed to produce chemical maps at the molecular level. Applications demonstrated herein include the examination of food sample surfaces, lifestyle chemistry, and chemical reactions on curved substrates. The modular design of this system also allows for modifications to the sampling probe and the ionization source, thereby expanding the potential of RoSA-MS for a great diversity of applications.
Eigendecomposition-based techniques are popular for a number of computer vision problems, e.g., object and pose estimation, because they are purely appearance based and they require few on-line computations. Unfortunately, they also typically require an unobstructed view of the object whose pose is being detected. The presence of occlusion and background clutter precludes the use of the normalizations that are typically applied and significantly alters the appearance of the object under detection. This work presents an algorithm that is based on applying eigendecomposition to a quadtree representation of the image dataset used to describe the appearance of an object. This allows decisions concerning the pose of an object to be based on only those portions of the image in which the algorithm has determined that the object is not occluded. The accuracy and computational efficiency of the proposed approach is evaluated on 16 different objects with up to 50% of the object being occluded and on images of ships in a dockyard.
This paper outlines the design of a portable manipulator system for use in remote detection and care of hemorrhage using High Intensity Focused Ultrasound (HIFU). We have developed a kinematically redundant manipulator that uses high fidelity force control for safe interaction with human patients. The manipulator is outfitted with a dual imaging and sonication end-effector for hemorrhage detection and treatment. Unlike most available force controlled manipulators, the design presented in this paper has all the actuation embedded inside its body eliminating the need for a base which greatly improves portability. We review the main design features, advantages, and trade-offs of this approach and present experimental data of hemorrhage detection and controlled sonication of biological tissue samples.978-1-4244-3804-4/09/$25.00 ©2009 IEEE
Energid is developing a realistic surgery simulator that delivers high fidelity visual and haptic feedback based on the physics of deformable objects. Modeling the interaction of surgical tools with soft biological tissue in real time poses challenges because the precise physical models of organs are not readily available, and the simulation of the behavior of tissue has a high computational burden. In this paper we present a realistic surgery simulation technique which inlcudes novel algorithms for simulating surgical palpation and cutting. We implement a meshfree numerical technique for realistic surgery palpation simulation. Simulation of surgical cutting is one of the most challenging tasks in the development of a surgery simulator. Changes in topology during simulation render precomputed data unusable. Moreover, the process is nonlinear and the underlying physics is complex. We propose a hybrid approach to the simulation of surgical cutting procedures by combining a node snapping technique with a physically based meshfree computational scheme.where J α is the nodal unknown at particle 'J'. The nodal shape function ( ) J h x at particle 'J' is generated using a moving least squares technique [20]: -1 ( ) = W ( ) ( ) ( ) ( ) T J J J References
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