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In this paper we propose a formal formulation for the estimation of Diffusion Tensors in the space of symmetric positive semidefinite (PSD) tensors. Traditionally, diffusion tensor model estimation has been carried out imposing tensor symmetry without constraints for negative eigenvalues. When diffusion weighted data does not follow the diffusion model, due to noise or signal drop, negative eigenvalues may arise. An estimation method that accounts for the positive definiteness is desirable to respect the underlying principle of diffusion. This paper proposes such an estimation method and provides a theoretical interpretation of the result. A closed-form solution is derived that is the optimal data-fit in the matrix 2-norm sense, removing the need for optimization-based tensor estimation.

Kinematic models of concentric tube robots have matured from considering only tube bending to considering tube twisting as well as external loading. While these models have been demonstrated to approximate actual behavior, modeling error can be significant for medical applications that often call for positioning accuracy of 1–2mm. As an alternative to moving to more complex models, this paper proposes using sensing to adaptively update model parameters during robot operation. Advantages of this method are that the model is constantly tuning itself to provide high accuracy in the region of the workspace where it is currently operating. It also adapts automatically to changes in robot shape and compliance associated with the insertion and removal of tools through its lumen. As an initial exploration of this approach, a recursive on-line estimator is proposed and evaluated experimentally.

The Kaczmarz method, or the algebraic reconstruction technique (ART), is a popular method for solving large-scale overdetermined systems of equations. Recently, Strohmer et al. proposed the randomized Kaczmarz algorithm, an improvement that guarantees exponential convergence to the solution. This has spurred much interest in the algorithm and its extensions. We provide in this paper an exact formula for the mean squared error (MSE) in the value reconstructed by the algorithm. We also compute the exponential decay rate of the MSE, which we call the “annealed” error exponent. We show that the typical performance of the algorithm is far better than the average performance. We define the “quenched” error exponent to characterize the typical performance. This is far harder to computethan the annealed error exponent, but we provide an approximation that matches empirical results. We also explore optimizing the algorithm’s row-selection probabilities to speed up the algorithm’s convergence., Engineering and Applied Sciences

Innovation in patient care requires both clinical and technical skills, and this paper presents the methods and outcomes of a nine-year, clinical-academic collaboration to develop and evaluate new medical device technologies, while teaching mechanical engineering. Together, over the course of a single semester, seniors, graduate students, and clinicians conceive, design, build, and test proof-of-concept prototypes. Projects initiated in the course have generated intellectual property and peer-reviewed publications, stimulated further research, furthered student and clinician careers, and resulted in technology licenses and start-up ventures.

Biological pathway maps are highly relevant tools for many tasks in molecular biology. They reduce the complexity of the overall biological network by partitioning it into smaller manageable parts. While this reduction of complexity is their biggest strength, it is, at the same time, their biggest weakness. By removing what is deemed not important for the primary function of the pathway, biologists lose the ability to follow and understand cross-talks between pathways. Considering these cross-talks is, however, critical in many analysis scenarios, such as judging effects of drugs. In this paper we introduce Entourage, a novel visualization technique that provides contextual information lost due to the artificial partitioning of the biological network, but at the same time limits the presented information to what is relevant to the analyst’s task. We use one pathway map as the focus of an analysis and allow a larger set of contextual pathways. For these context pathways we only show the contextual subsets, i.e., the parts of the graph that are relevant to a selection. Entourage suggests related pathways based on similarities and highlights parts of a pathway that are interesting in terms of mapped experimental data. We visualize interdependencies between pathways using stubs of visual links, which we found effective yet not obtrusive. By combining this approach with visualization of experimental data, we can provide domain experts with a highly valuable tool. We demonstrate the utility of Entourage with case studies conducted with a biochemist who researches the effects of drugs on pathways. We show that the technique is well suited to investigate interdependencies between pathways and to analyze, understand, and predict the effect that drugs have on different cell types., Engineering and Applied Sciences

Surgical robots are gaining favor in part due to their capacity to reach remote locations within the body. Continuum robots are especially well suited for accessing deep spaces such as cerebral ventricles within the brain. Due to the entry point constraints and complicated structure, current techniques do not allow surgeons to access the full volume of the ventricles. The ability to access the ventricles with a dexterous robot would have significant clinical implications. This paper presents a concentric tube manipulator mated to a robotically controlled flexible endoscope. The device adds three degrees of freedom to the standard neuroendoscope and roboticizes the entire package allowing the operator to conveniently manipulate the device. To demonstrate the improved functionality, we use an in-silica virtual model as well as an ex-vivo anatomic model of a patient with a treatable form of hydrocephalus. In these experiments we demonstrate that the augmented and roboticized endoscope can efficiently reach critical regions that a manual scope cannot.

Three dimensional ultrasound is a promising imaging modality for minimally invasive robotic surgery. As the robots are typically metallic, they interact strongly with the sound waves in ways that are not modeled by the ultrasound system’s signal processing algorithms. Consequently, they produce substantial imaging artifacts that can make image guidance difficult, even for experienced surgeons. This paper introduces a new approach for detecting curved continuum robots in 3D ultrasound images. The proposed approach combines geodesic active contours with a speed function that is based on enhancing the “tubularity” of the continuum robot. In particular, it takes advantage of the known robot diameter along its length. It also takes advantage of the fact that the robot surface facing the ultrasound probe provides the most accurate image. This method, termed Tubular Enhanced Geodesic Active Contours (TEGAC), is demonstrated through ex vivo intracardiac experiments to offer superior performance compared to conventional active contours.

Strokes affect over 750,000 people annually in the United States. This significant and disabling condition can result in paralysis that must be treated by regular sessions with a dedicated physical therapist in order to regain motor function. However, the use of therapists is expensive, in high demand, and requires patient travel to a rehabilitation clinic. We propose an inexpensive and wearable upper body orthotics system that can be used at home to provide the same level of rehabilitation as the current physical therapy standard of care. The system is composed of a soft orthotic device with an integrated cable actuation system that is worn over the upper body, a limb position sensing system, and an actuator package. This paper presents initial design considerations and the evaluation of a proof of concept system for shoulder joint rehabilitation. Through simulations and experimental evaluation, the system is shown to be adjustable, easily wearable, and adaptable to misalignment and anatomical variations. Insights provided by these initial studies will inform the development of a complete upper body orthotic system., Engineering and Applied Sciences

Concentric tube robots are a novel class of continuum robots that are constructed by combining pre-curved elastic tubes such that the overall shape of the robot is a function of the relative rotations and translations of the constituent tubes. Frictionless kinematic and quasistatic force models for this class of robots have been developed that incorporate bending and twisting of the tubes. Experimental evaluation of these models has revealed, however, a directional dependence of tube rotation on robot shape that is not predicted by these models. To explain this behavior, this paper models the contributions of friction arising from two sources: the distributed forces of contact between the tubes along their length and the concentrated bending moments generated at discontinuities in curvature and at the boundaries. It is shown that while friction due to distributed forces is insufficient to explain the experimentally observed tube twisting, a simple model of frictional torque arising from concentrated moments provides a good match with the experimental data.

Replacing open-heart surgical procedures with beating-heart interventions substantially decreases the trauma and risk of a procedure. One of the most challenging procedures to perform on the beating heart is valve repair. To address this need, this paper proposes a tool for replacing mitral valve chordae to correct regurgitation. The chordae is secured to the papillary muscle and leaflet using NiTi tissue anchors that also incorporate an internal adjustment mechanism to enable initial adjustment as well as subsequent readjustment of chordae length. Efficacy of the proposed tool for chordae replacement and reduction of regurgitation was demonstrated in an ex-vivo heart simulator.

Three-dimensional ultrasound has been an effective imaging modality for diagnostics and is now an emerging modality for image-guided minimally-invasive interventions since it enables visualization of both instruments and tissue. Challenges to ultrasound-guided interventions arise, however, due to the low signal-to-noise ratio and the imaging artifacts created by the interventional instruments. Metallic instruments, in particular, are strong scatters and so produce a variety of artifacts. For many interventions, the manual or robotic instrument is comprised of a long curved tubular structure with specialized tooling at its tip. Toward the goal of developing a surgical navigation system, this paper proposes an image processing algorithm for enhancing the tubular structure of imaged instruments while also reducing imaging artifacts. Experiments are presented to evaluate the effectiveness of the approach in the context of robotic instruments whose shape comprises a smooth curve along their length.

Achieving superior outcomes through the use of robots in medical applications requires an integrated approach to the design of the robot, tooling and the procedure itself. In this paper, this approach is applied to develop a robotic technique for closing abnormal communication between the atria of the heart. The goal is to achieve the efficacy of surgical closure as performed on a stopped, open heart with the reduced risk and trauma of a beating-heart catheter-based procedure. In the proposed approach, a concentric tube robot is used to percutaneously access the right atrium and deploy a tissue approximation device. The device is constructed using a metal MEMS fabrication process and is designed to both fit the manipulation capabilities of the robot as well as to reproduce the beneficial features of surgical closure by suture. Experimental results demonstrate device efficacy through manual in-vivo deployment and bench-top robotic deployment.

Concentric tube robots are a subset of continuum robots constructed by combining pre-curved elastic tubes. As the tubes are rotated and translated with respect to each other, their curvatures interact elastically, enabling control of the robot's tip configuration as well as the curvature along its length. This technology is projected to be useful in many types of minimally invasive medical procedures. Because these robots are flexible by design, they deflect considerably when applying forces to the external environment. Thus, in contrast to rigid-link robots, their kinematic and static force models are coupled. This paper derives a multi-tube quasistatic model that relates tube rotations and translations together with externally applied loads to robot shape and tip configuration. The model can be applied in robot design, procedure planning as well as control. For validation, the multi-tube model is compared experimentally to a computationally-efficient single-tube approximate model.

Stiffness control of a continuum robot can prevent excessive contact forces during robot navigation inside delicate, uncertain and confined environments. Furthermore, it enables the selection of tip stiffnesses that match varying task requirements. This paper introduces a computationally-efficient approach to continuum-robot stiffness control that is based on writing the forward kinematic model as the product of two transformations. The first transformation calculates the non-contact kinematics of the robot and can be formulated based on the specific type of continuum robot under consideration. The second transformation calculates the tip deflection due to applied forces and is efficiently computed using the special Cosserat rod model. To implement a desired tip stiffness, the two transformations are used to solve for the actuator positions that deform the manipulator so as to generate the required tip force at the measured tip position. The efficacy of the proposed controller is demonstrated experimentally on a concentric-tube continuum robot.