A new scheme of data-driven segmentation is proposed, which is based on detection of object boundary, and volumetric pattern reconstruction as implicit function by using the detected object boundary and the radial basis functions (RBF). By using clinical X-ray CT data, applications in visualization of the pancreatic duct by MINIP of curved thin-slab and in liver segmentation are shown.

1 Implementing Radial Basis Functions Using Bump-Resistor Networks John G. Harris University of Florida EE Dept., 436 CSE Bldg 42 Gainesville, FL 32611 [email protected] .edu Abstract| Radial Basis Function (RBF) networks provide a powerful learning architecture for neural networks [6]. We have implemented a RBF network in analog VLSI using the concept of bump-resistors. A bump-resistor is a ...

Adaptive communication is one of the methods used for high rate communication with efficient spectrum efficiency and with improved accuracy for future wireless communication systems. In this paper, we propose an adaptive modulated Orthogonal Frequency Division Multiplexing (OFDM) system based on Radial Basis Function (RBF) and then their performance (MSE) and classification accuracy is evaluate...

We have developed a new algorithm, RBF-MREIT, for Magnetic Resonance Electrical Impedance Tomography (MREIT) by applying the radial basis function (RBF) network and Simplex method. RBF-MREIT uses only one component of the measured magnetic flux density to reconstruct the conductivity images, and provides a solution to the rotation problem in MREIT. The proposed algorithm is tested on a three-sp...

Despite such very appealing features of the radial basis function (RBF) as inherent meshfree and independent of dimension and geometry, the various RBF-based schemes [1] of solving partial differential equations (PDE’s) still confront some deficiencies. For instances, the lack of easy-to-use spectral convergent RBFs, ill-conditioning and costly evaluation of full interpolation matrix. The purpo...

in this article, we apply the multiquadric radial basis function (rbf) interpo-lation method for nding the numerical approximation of traveling wave solu-tions of the kawahara equation. the scheme is based on the crank-nicolsonformulation for space derivative. the performance of the method is shown innumerical examples.

The performance of radial basis function decision feedback equalised burst-by-burst adaptive modulation is presented for transmission over dispersive wideband mobile channels. Radial Basis Function (RBF) network based channel equalisers have a close relationship with Bayesian schemes. The RBF decision feedback equaliser (RBF DFE) is capable of estimating the 'short term bit error rate' of the r...

This paper proposes a Neural Network model using Generalised kernel functions for the hidden layer of a feed forward network. These functions are Generalised Radial Basis Functions (GRBF), and the architecture, weights and node topology are learned through an evolutionary algorithm. The proposed model is compared with the corresponding standard hidden-node models: Product Unit (PU) neural netwo...

in this paper, a technique generally known as meshless numerical scheme for solving fractional dierential equations isconsidered. we approximate the exact solution by use of radial basis function(rbf) collocation method. this techniqueplays an important role to reduce a fractional dierential equation to a system of equations. the numerical results demonstrate the accuracy and ability of this me...

in the present paper, a numerical method is considered for solving one-dimensionalheat equation subject to both neumann and dirichlet initial boundaryconditions. this method is a combination of collocation method and radial basis functions (rbfs). the operational matrix of derivative for laguerre-gaussians (lg) radial basis functions is used to reduce the problem to a set of algebraic equations...