Kismet Anak Hong Ping

Advances in the 3-D Forward–Backward Time-Stepping (FBTS) Inverse Scattering Technique for Breast Cancer Detection

This paper presents recent advances in a 3-D inverse scattering technique, called forward-backward time-stepping (FBTS), applied to the reconstruction of the microwave properties of the breast. The FBTS algorithm is utilized for a numerical-based study of a 3-D breast model based on an MRI. Several illumination schemes, based on different microwave transmitter/receiver configurations, are compared based on the quality of the reconstructed images of the breast model. A combination of cylindrical and planar arrays is shown to provide accurate estimates of the model electrical parameters that delineate the various regions of the breast. Although further analysis with this combination array demonstrates that tumors of reduced size and reduced contrast with the surrounding fibroglandular region are much more difficult (and in some cases not possible) to reconstruct, the study presents some promising initial results of a reconstruction technique for breast imaging and cancer detection.

Microwave breast imaging by the filtered forward-backward time-stepping method

In this paper, an inverse scattering technique referred to as the filtered forward-backward time-stepping method is applied to microwave imaging for breast cancer detection. A two-dimensional numerical breast phantom (derived from MR images) with high contrast between fat and fibroglandular tissues, and low contrast between fibroglandular and tumor tissues are used to assess the efficacy of the proposed method.

Two-dimensional Forward-Backward Time-Stepping approach for tumor detection in dispersive breast tissues

The Forward-Backward Time-Stepping (FBTS) technique is applied to determine the presence and location of malignant tumor in the heterogeneous breast model. A new strategy is integrated in the FBTS algorithm to accurately estimate the dielectric properties of tissues. We demonstrate 2-D FBTS technique utilizing the numerical dispersive breast model in a free space. This new strategy manipulating Debye dispersion equation is proposed to treat dispersive case. Numerical simulation results show the FBTS algorithm has the potential to provide useful quantitative information of the breasts internal composition.

Preliminary study of Forward-Backward Time-Stepping technique with edge-preserving regularization for object detection applications

Forward-Backward Time-Stepping (FBTS) technique is used for the detection, imaging and reconstruction of an embedded object which is formulated at the time-domain utilizing Finite-Difference Time-Domain (FDTD) method. In order to solve FBTS inverse scattering problem, edge-preserving regularization is integrated. Image reconstruction results illustrated that the FBTS integrated with an edge-preserving regularization technique has the potential to detect the presence of the embedded object accurately. In this paper, an extended algorithm is shown in time-domain image reconstruction.

Preliminary Results on Estimation of the Dispersive Dielectric Properties of an Object Utilizing Frequency-Dependent Forward-Backward Time-Stepping Technique

In this paper, a Frequency-Dependent Forward-Backward Time-Stepping (FD-FBTS) inverse scattering technique is used for reconstruction of homogeneous dispersive object. The aim of the technique is to reconstruct the relative permittivity at infinite frequency, static relative permittivity and static conductivity of the homogeneous dispersive object simultaneously. The technique utilizes iterative finite-difference time-domain (FDTD) method for solving inverse scattering problem in time domain. The minimization of the cost functional is carried out utilizing Dai-Yuan nonlinear conjugate-gradient algorithm. The Frechet derivatives of the augmented cost functional are derived analytically with respect to scatterer properties. Numerical results for reconstruction of two-dimensional homogeneous dispersive illustrate the performance of the proposed technique.

Preliminary Results of Integrating Tikhonov’s Regularization in Forward-Backward Time-Stepping Technique for Object Detection

The inverse scattering in time domain known as Forward-Backward Time-Stepping (FBTS) technique is applied to determine the sizes, shape and location of the embedded objects. Tikhonov’s regularization method has been proposed in order to improve or solve the ill-posed of FBTS inverse scattering problem. The reconstructed results showed that FBTS technique can detect the presence of embedded objects. The reconstructed results of FBTS technique utilizing with the Tikhonov’s regularization method shown better results than the results only applied FBTS technique. Tikhonov’s regularization combined with FBTS technique to improve the quality of image reconstruction.

Elliptic Filter and Iterative Inversion Method for Buried Object Detection Applications

In this paper, Forward-Backward Time-Stepping (FBTS) inversion method is used for detection, imaging and reconstruction of an unknown object in a region of interest. We consider the reconstruction parameter profiles of two-dimensional objects from measurement of the transient total electromagnetic field data contaminated with noise. A preliminary result of an Elliptic filter integrated in FBTS algorithm to suppress noise effect has been obtained. A circular shape in the region of interest is successfully detected and reconstructed.

Integration of Image Segmentation Method in Inverse Scattering for Brain Tumour Detection

This paper presents a microwave imaging for brain tumour detection utilizing ForwardBackward Time-Stepping (FBTS) inverse scattering technique. This technique is applied to solve electromagnetic scattered signals. It is proven that this technique is able to detect the presence of tumour in the breast. The application is now extended to brain imaging. Two types of results are presented in this paper; FBTS and FBTS integrated with image segmentation as a pre-processing step to form a focusing reconstruction. The results show that the latter technique has improved the reconstructions compared to the primary technique. Integration of the image segmentation step helps to reduce the variation of the estimated dielectric properties of the head tissues. It is also found that the optimal frequency used for microwave brain imaging is at 2 GHz and able to detect a tumour as small as 5 mm in diameter. The numerical simulations show that the integration of image segmentation with FBTS has the potential to provide useful quantitative information on the head internal composition.

Profile Reconstruction Utilizing Forward-Backward Time-Stepping With the Integration of Automated Edge-Preserving Regularization Technique for Object Detection Applications

A regularization is integrated with Forward-Backward Time-Stepping (FBTS) method which is formulated in time-domain utilizing Finite-Difference Time-Domain (FDTD) method to solve the nonlinear and ill-posed problem arisen in the microwave inverse scattering problem. FBTS method based on a Polak-Ribiete-Polyak conjugate gradient method is easily trapped in the local minima. Thus, we extend our work with the integration of edge-preserving regularization technique due to its ability to smooth and preserve the edges containing important information for reconstructing the dielectric profiles of the targeted object. In this paper, we propose a deterministic relaxation with Mean Square Error algorithm known as DrMSE in FBTS and integrate it with the automated edge-preserving regularization technique. Numerical simulations are carried out and prove that the reconstructed results are more accurate by calculating the edge-preserving parameter automatically.

Data Acquisition System Hardware for GPS Propagation Sentences in Less Developed Countries: A Review

GPS receivers play an important role for calculating and determining the precise point positioning and deal with the navigational messages. Also, one of the main uses of high-end GPS receivers is for scientific research and space science analysis. The handheld GPS receivers were utilized for experimental purposes contrary to the traditional application for recreation and geo-catching activities. The classification of different commercial GPS receivers gave an inside idea for application and utilization of these receivers in the field of laboratory research. Garmin GPS handheld receivers performed an excellent example in conducting experimental work for GPS propagation data analysis.