Myoung Hwan Choi

A Reconstruction Algorithm for Breast Cancer Imaging With Electrical Impedance Tomography in Mammography Geometry

The conductivity and permittivity of breast tumors are known to differ significantly from those of normal breast tissues, and electrical impedance tomography (EIT) is being studied as a modality for breast cancer imaging to exploit these differences. At present, X-ray mammography is the primary standard imaging modality used for breast cancer screening in clinical practice, so it is desirable to study EIT in the geometry of mammography. This paper presents a forward model of a simplified mammography geometry and a reconstruction algorithm for breast tumor imaging using EIT techniques. The mammography geometry is modeled as a rectangular box with electrode arrays on the top and bottom planes. A forward model for the electrical impedance imaging problem is derived for a homogeneous conductivity distribution and is validated by experiment using a phantom tank. A reconstruction algorithm for breast tumor imaging based on a linearization approach and the proposed forward model is presented. It is found that the proposed reconstruction algorithm performs well in the phantom experiment, and that the locations of a 5-mm-cube metal target and a 6-mm-cube agar target could be recovered at a target depth of 15 mm using a 32 electrode system

A real-time traffic control scheme of multiple AGV systems for collision free minimum time motion: a routing table approach

A two-staged traffic control scheme, in which sets of candidate paths are prepared off-line prior to overall motion planning process, has been widely adopted for motion planning of mobile robots, but relatively little attention has been given to the application of the two-staged scheme to multiple automated guided vehicle systems (MAGVSs). In the paper, a systematic two-staged traffic control scheme is presented to obtain collision-free minimum-time motions of AGVs along loopless paths. The overall structure of the controller is divided into two tandem modules of off-line routing table generator (RTG) and an online traffic controller (OTC). First, an induced network model is established considering the configurational restrictions of guide-paths. With this model and a modified k-shortest path algorithm, RTG finds sets of k candidate paths from each station nodes to all the other station nodes off-line and stores them in the form of routing tables. Each time a dispatch command for an AGV is issued, OTC utilizes these routing tables to generate a collision-free minimum-time motion along a loopless path. Real-time computation is guaranteed in that the time-consuming graph searching process is executed off-line by RTG, and OTC looks for the minimum time motion among the k candidate paths. The traffic control scheme proposed is suitable for practical application in centralized MAGVS with zone blocking technique.

Probabilistic map merging for multi-robot rbpf-slam with unknown initial poses

This paper addresses the map merging problem, which is the most important issue in multi-robot simultaneous localization and mapping (SLAM) using the Rao-Blackwellized particle filter (RBPF-SLAM) with unknown initial poses. The map merging is performed using the map transformation matrix and the pair of map merging bases (MMBs) of the robots. However, it is difficult to find appropriate MMBs because each robot pose is estimated under multi-hypothesis in the RBPF-SLAM. In this paper, probabilistic map merging (PMM) using the Gaussian process is proposed to solve the problem. The performance of PMM was verified by reducing errors in the merged map with computer simulations and real experiments.

Regional Admittivity Spectra With Tomosynthesis Images for Breast Cancer Detection: Preliminary Patient Study

Because the electrical properties of many breast tumors are different from those of surrounding, normal tissue, imaging these properties may provide useful diagnostic information. At the present time, X-ray mammography is the standard imaging modality used for breast cancer screening. The interpretation of EIT imaging is thus enhanced by its use together with X-ray mammography in the same geometry. This paper reports the ability of electrical impedance spectroscopy (EIS) to localize and distinguish cancers from normal tissues. These findings are confirmed by simultaneous, co-registered 3-D mammograms or tomosynthesis images and are verified with biopsy reports.

A force/moment sensor for intuitive robot teaching application

This paper presents the development of a force/moment sensor named COSMO-II that can be used in the intuitive robot teaching of a six axis robot. A new principle of force/moment detection is presented that uses force sensing resistor as the transducer. The function of the COSMO-II sensor is to detect the force and moment about the principal axes of the the sensor coordinate system, so that the sensor information can be used for the intuitive robot teaching. The architecture and force/moment detection principle and the developed prototype sensor are describe. The performance of the sensor is evaluated and the results are shown. The sensor architecture is simple and can be implemented at low cost.

Resolving kinematic redundancy of a robot using a quadratically constrained optimization technique

The constraints on the physical limit should be considered in a kinematic redundancy resolution problem of a robot. This paper proposes a new optimization scheme to resolve kinematic redundancy of the robot while considering physical constraints. In the proposed scheme, quadratic inequality constraints are used in place of linear inequality constraints, thus a quadratically constrained optimization technique is applied to resolve the redundancy. It is shown that the use of quadratic inequality constraints considerably reduces the number of constraints. Therefore, the proposed method reduces the problem size considerably and makes the problem simple resulting in computational efficiency. A numerical example of a 4hlink planar redundant robot is included to demonstrate the efficiency of the proposed optimization technique. In this example, simulation results using the proposed method and another wellhknown method are compared and discussed.

Acoustic lens error compensation in ultrasonic probes for spatial compounding using image registration

Spatial compounding is an speckle reducing imaging technique in which a number of ultrasound images of a given target that have been obtained from multiple angles are combined into a single compounded image by combining the data received from each data point in the compounded image. The ultrasonic beams are steered at desired angles electronically by controlling the ultrasonic transducer element arrays. The ultrasonic beam produced by the transducer array undergoes refraction at the surface of the acoustic lens. However, since the acoustic properties of the acoustic lens are not known exactly, the exact refraction is not known. The uncertainties in the refraction angle leads to the image position error and results in the blurring of the compounded images. In this paper, we study a compensation method using image registration that can reduce the lens artifact.

An iterative approach for applying multiple currents to a body using voltage sources in electrical impedance tomography

An approach for using voltage sources to produce a desired current pattern in an ACT-type EIT system is presented. An iterative adaptive algorithm generates the necessary voltage pattern that will result in the desired current pattern. The convergence of the algorithm is shown under the condition that the estimation error of the linear mapping from voltage to current is small. The simulation results are presented along with the implication of the convergence condition.

An application of force ellipsoid to the optimal load distribution for two cooperating robots

The optimal load distribution for two cooperating robots is studied, and a solution approach utilizing a force ellipsoid is presented. The load distribution problem is formulated as a nonlinear optimization problem with a quadratic cost function. The effort exerted by the robots to follow the specified motion is defined to be the joint torque norm square, and the optimal solution minimizing the effort is obtained using the concept of the force ellipsoid and nonlinear optimization theory. Despite the presence of the joint torque constraints, the optimal solution is obtained almost as a closed form which requires small computation time. The proposed solution approach is illustrated and the internal force effect is studied using a numerical example.<<ETX>>

A real time traffic control scheme for a multiple AGV system

The conflict-free minimum-time motion planning problem in a multiple AGV system using zone control requires a traffic control scheme based upon a non-search technique, since the number of nodes contained in the network model for its guidepath is considerably large. The traffic control scheme presented in this paper partitions the overall task into two constituent tasks of path generation and traffic control. The Path Generator employs a k-shortest path search algorithm to construct path sets between all possible station node pairs. The path generation process is performed in off-line. Occupation times for each link are calculated and stored in a link occupation table which is represented from a link-oriented viewpoint. The traffic controller examines the link occupation table and dispatches AGVs in a conflict-free minimum-time path. The on-line motion planning operation is performed in real time.