3D microwave tomography with huber regularization applied to realistic numerical breast phantoms

Quantitative active microwave imaging for breast cancer screening and therapy monitoring applications requires adequate reconstruction algorithms, in particular with regard to the nonlinearity and ill-posedness of the inverse problem. We employ a fully vectorial three-dimensional nonlinear inversion algorithm for reconstructing complex permittivity profiles from multi-view single-frequency scattered field data, which is based on a Gauss-Newton optimization of a regularized cost function. We tested it before with various types of regularizing functions for piecewise-constant objects from Institut Fresnel and with a quadratic smoothing function for a realistic numerical breast phantom. In the present paper we adopt a cost function that includes a Huber function in its regularization term, relying on a Markov Random Field approach. The Huber function favors spatial smoothing within homogeneous regions while preserving discontinuities between contrasted tissues. We illustrate the technique with 3D reconstructions from synthetic data at 2GHz for realistic numerical breast phantoms from the University of Wisconsin-Madison UWCEM online repository: we compare Huber regularization with a multiplicative smoothing regularization and show reconstructions for various positions of a tumor, for multiple tumors and for different tumor sizes, from a sparse and from a denser data configuration

A microparticle swarm optimizer for the reconstruction of microwave images

A novel optimization technique known as the microparticle swarm optimizer (μPSO) is proposed for high-dimensional microwave image reconstruction. With the proposed μPSO, good optimization performance can be obtained especially for solving high-dimensional optimization problems. In addition, the proposed μPSO requires only a small population size to outperform the standard PSO that uses a larger population size. Our simulation results on the reconstruction of the dielectric properties of normal and malignant breast tissues have shown that the μPSO can perform quite well for this high-dimensional microwave image reconstruction problem. © 2007 IEEE

Importance of phase unwrapping for the reconstruction of microwave tomographic images

Microwave image reconstruction is typically based on a regularized least-square minimization of either the complex-valued field difference between recorded and modeled data or the logarithmic transformation of these field differences. Prior work has shown anecdotally that the latter outperforms the former in limited surveys of simulated and experimental phantom results. In this paper, we provide a theoretical explanation of these empirical findings by developing closed form solutions for the field and the inverted electromagnetic property parameters in one dimension which reveal the dependency of the estimated permittivity and conductivity on the absolute (unwrapped) phase of the measured signal at the receivers relative to the source transmission. The analysis predicts the poor performance of complex-valued field minimization as target size and/or frequency and electromagnetic contrast increase. Such poor performance is avoided by logarithmic transformation and preservation of absolute measured signal phase. Two-dimensional experiments based on both synthetic and clinical data are used to confirm these findings. Robustness of the logarithmic transformation to variation in the initial guess of the reconstructed target properties is also shown. The results are generalizable to three dimensions and indicate that the minimization form with logarithmic transformation offers image reconstruction performance characteristics that are much more desirable for medial microwave imaging applications relative to minimizing differences in complex-valued field quantities

Optimal reference sequence selection for genome assembly using minimum description length principle

Reference assisted assembly requires the use of a reference sequence, as a model, to assist in the assembly of the novel genome. The standard method for identifying the best reference sequence for the assembly of a novel genome aims at counting the number of reads that align to the reference sequence, and then choosing the reference sequence which has the highest number of reads aligning to it. This article explores the use of minimum description length (MDL) principle and its two variants, the two-part MDL and Sophisticated MDL, in identifying the optimal reference sequence for genome assembly. The article compares the MDL based proposed scheme with the standard method coming to the conclusion that “counting the number of reads of the novel genome present in the reference sequence” is not a sufficient condition. Therefore, the proposed MDL scheme includes within itself the standard method of “counting the number of reads that align to the reference sequence” and also moves forward towards looking at the model, the reference sequence, as well, in identifying the optimal reference sequence. The proposed MDL based scheme not only becomes the sufficient criterion for identifying the optimal reference sequence for genome assembly but also improves the reference sequence so that it becomes more suitable for the assembly of the novel genome

Application-Specific Broadband Antennas for Microwave Medical Imaging

The goal of this work is the introduction of efficient antenna structures on the basis of the requirement of different microwave imaging methods; i.e. quantitative and qualitative microwave imaging techniques. Several criteria are proposed for the evaluation of single element antenna structures for application in microwave imaging systems. The performance of the proposed antennas are evaluated in simulation and measurement scenarios

UWB Pulse Radar for Human Imaging and Doppler Detection Applications

We were motivated to develop new technologies capable of identifying human life through walls. Our goal is to pinpoint multiple people at a time, which could pay dividends during military operations, disaster rescue efforts, or assisted-living. Such system requires the combination of two features in one platform: seeing-through wall localization and vital signs Doppler detection. Ultra-wideband (UWB) radar technology has been used due to its distinct advantages, such as ultra-low power, fine imaging resolution, good penetrating through wall characteristics, and high performance in noisy environment. Not only being widely used in imaging systems and ground penetrating detection, UWB radar also targets Doppler sensing, precise positioning and tracking, communications and measurement, and etc. A robust UWB pulse radar prototype has been developed and is presented here. The UWB pulse radar prototype integrates seeing-through imaging and Doppler detection features in one platform. Many challenges existing in implementing such a radar have been addressed extensively in this dissertation. Two Vivaldi antenna arrays have been designed and fabricated to cover 1.5-4.5 GHz and 1.5-10 GHz, respectively. A carrier-based pulse radar transceiver has been implemented to achieve a high dynamic range of 65dB. A 100 GSPS data acquisition module is prototyped using the off-the-shelf field-programmable gate array (FPGA) and analog-to-digital converter (ADC) based on a low cost solution: equivalent time sampling scheme. Ptolemy and transient simulation tools are used to accurately emulate the linear and nonlinear components in the comprehensive simulation platform, incorporated with electromagnetic theory to account for through wall effect and radar scattering. Imaging and Doppler detection examples have been given to demonstrate that such a “Biometrics-at-a-glance” would have a great impact on the security, rescuing, and biomedical applications in the future

Information Theory, Graph Theory and Bayesian Statistics based improved and robust methods in Genome Assembly

Bioinformatics skills required for genome sequencing often represent a significant hurdle for many researchers working in computational biology. This dissertation highlights the significance of genome assembly as a research area, focuses on its need to remain accurate, provides details about the characteristics of the raw data, examines some key metrics, emphasizes some tools and outlines the whole pipeline for next-generation sequencing. Currently, a major effort is being put towards the assembly of the genomes of all living organisms. Given the importance of comparative genome assembly, herein dissertation, the principle of Minimum Description Length (MDL) and its two variants, the Two-Part MDL and Sophisticated MDL, are explored in identifying the optimal reference sequence for genome assembly. Thereafter, a Modular Approach to Reference Assisted Genome Assembly Pipeline, referred to as MARAGAP, is developed. MARAGAP uses the principle of Minimum Description Length (MDL) to determine the optimal reference sequence for the assembly. The optimal reference sequence is used as a template to infer inversions, insertions, deletions and Single Nucleotide Polymorphisms (SNPs) in the target genome. MARAGAP uses an algorithmic approach to detect and correct inversions and deletions, a De-Bruijn graph based approach to infer insertions, an affine-match affine-gap local alignment tool to estimate the locations of insertions and a Bayesian estimation framework for detecting SNPs (called BECA). BECA effectively capitalizes on the `alignment-layout-consensus' paradigm and Quality (Q-) values for detecting and correcting SNPs by evaluating a number of probabilistic measures. However, the entire process is conducted once. BECA's framework is further extended by using Gibbs Sampling for further iterations of BECA. After each assembly the reference sequence is updated and the probabilistic score for each base call renewed. The revised reference sequence and probabilities are then further used to identify the alignments and consensus sequence, thereby, yielding an algorithm referred to as Gibbs-BECA. Gibbs-BECA further improves the performance both in terms of rectifying more SNPs and offering a robust performance even in the presence of a poor reference sequence. Lastly, another major effort in this dissertation was the development of two cohesive software platforms that combine many different genome assembly pipelines in two distinct environments, referred to as Baari and Genobuntu, respectively. Baari and Genobuntu support pre-assembly tools, genome assemblers as well as post-assembly tools. Additionally, a library of tools developed by the authors for Next Generation Sequencing (NGS) data and commonly used biological software have also been provided in these software platforms. Baari and Genobuntu are free, easily distributable and facilitate building laboratories and software workstations both for personal use as well as for a college/university laboratory. Baari is a customized Ubuntu OS packed with the tools mentioned beforehand whereas Genobuntu is a software package containing the same tools for users who already have Ubuntu OS pre-installed on their systems