Spherical harmonics microwave algorithm for shape and location reconstruction of breast cancer tumor

Three-dimensional iterative reconstruction of pulsed radiation sources using spherical harmonic decomposition

Neutron and x-ray imaging are essential ways to diagnose a pulsed radiation source. The three-dimensional (3D) intensity distribution reconstructed from two-dimensional (2D) radiation images can significantly promote research regarding the generation and variation mechanisms of pulsed radiation sources. Only a few (≤5) projected images at one moment are available due to the difficulty in building imaging systems for high-radiation-intensity and short-pulsed sources. The reconstruction of a 3D source with a minimal number of 2D images is an ill-posed problem that leads to severe structural distortions and artifacts of the image reconstructed by conventional algorithms. In this paper, we present an iterative method to reconstruct a 3D source using spherical harmonic decomposition. Our algorithm improves the representation ability of spherical harmonic decomposition for 3D sources by enlarging the order of the expansion, which is limited in current analytical reconstruction algorithms. Prior knowledge of the source can be included to obtain a reasonable solution. Numerical simulations demonstrate that the reconstructed image quality of the iterative algorithm is better than that of the analytical algorithm. The iterative method can suppress the effect of noise in the integral projection image and has better robustness and adaptability than the analytical method.

Microwave imaging of human forearms: pilot study and image enhancement

We present a pilot study using a microwave tomography system in which we image the forearms of 5 adult male and female volunteers between the ages of 30 and 48. Microwave scattering data were collected at 0.8 to 1.2 GHz with 24 transmitting and receiving antennas located in a matching fluid of deionized water and table salt. Inversion of the microwave data was performed with a balanced version of the multiplicative-regularized contrast source inversion algorithm formulated using the finite-element method (FEM-CSI). T1-weighted MRI images of each volunteer's forearm were also collected in the same plane as the microwave scattering experiment. Initial “blind” imaging results from the utilized inversion algorithm show that the image quality is dependent on the thickness of the arm's peripheral adipose tissue layer; thicker layers of adipose tissue lead to poorer overall image quality. Due to the exible nature of the FEM-CSI algorithm used, prior information can be readily incorporated into the microwave imaging inversion process. We show that by introducing prior information into the FEM-CSI algorithm the internal anatomical features of all the arms are resolved, significantly improving the images. The prior information was estimated manually from the blind inversions using an ad hoc procedure.

A study of matching fluid loss in a biomedical microwave tomography system

PURPOSE

Effective imaging of human tissue with microwave tomography systems requires a matching fluid to reduce the wave reflections at the tissue boundary. Further, in order to match the idealized mathematical model used for imaging with the complicated physical measurement environment, loss must be added to the matching fluid. Both too little and too much loss result in low-quality images, but due to the nonlinear nature of the imaging problem, the exact nature of loss-to-image quality cannot be predicted a priori. Possible optimal loss levels include a single, highly sensitive value, or a broad range of acceptable losses. Herein, the authors outline a process of determining an appropriate level of loss inside the matching fluid and attempt to determine the bounds for which the images are the highest quality.

METHODS

Our biomedical microwave tomography system is designed for 2D limb imaging, operating from 0.8 to 1.2 GHz. Our matching fluid consists of deionized water with various levels of loss introduced by the addition of table salt. Using two homogeneous tissue-mimicking phantoms, and eight different matching fluids of varying salt concentrations, the authors introduce quantitative image quality metrics based on L-norms, mean values, and standard deviations to test the tomography system and assess image quality. Images are generated with a balanced multiplicative regularized contrast source inversion algorithm. The authors further generate images of a human forearm which may be analyzed qualitatively.

RESULTS

The image metrics for the phantoms support the claim that the worst images occur at the extremes of high and low salt concentrations. Importantly, the image metrics show that there exists a broad range of salt concentrations that result in high-quality images, not a single optimal value. In particular, 2.5-4.5 g of table salt per liter of deionized water provide the best reconstruction quality for simple phantoms. The authors argue that qualitatively, the human forearm data provide the best images at approximately the same salt concentrations.

CONCLUSIONS

There exists a relatively large-range of matching fluid losses (i.e., salt concentrations) that provide similar image quality. In particular, it is not necessary to spend time highly optimizing the level of loss in the matching fluid.

Review of electromagnetic techniques for breast cancer detection

Breast cancer is anticipated to be responsible for almost 40,000 deaths in the USA in 2011. The current clinical detection techniques suffer from limitations which motivated researchers to investigate alternative modalities for the early detection of breast cancer. This paper focuses on reviewing the main electromagnetic techniques for breast cancer detection. More specifically, this work reviews the cutting edge research in microwave imaging, electrical impedance tomography, diffuse optical tomography, microwave radiometry, biomagnetic detection, biopotential detection, and magnetic resonance imaging (MRI). The goal of this paper is to provide biomedical researchers with an in-depth review that includes all main electromagnetic techniques in the literature and the latest progress in each of these techniques.

Electromagnetic imaging within the contrast-source formulation by means of the multiscaling inexact Newton method

We introduce a new imaging technique that integrates the inexact Newton method into a multifocusing scheme within the contrast-source formulation of the inverse scattering problem. Representative results from an extensive validation concerned with both synthetic and experimental scattering data are reported to assess, also through comparisons, advantages and limitations of the proposed approach in terms of accuracy, robustness, and computational efficiency.

Microwave imaging for early breast cancer detection using a shape-based strategy

In this paper, we propose and analyze a novel shape reconstruction technique for the early detection of breast cancer from microwave data, which is based on a level-set technique. The shape-based approach offers several advantages compared to more traditional pixel-based approaches when targeting the reconstruction of key characteristics of a hidden tumor such as its correct size, shape, and static permittivity value. In addition to these key characteristics of hidden tumors, we aim at estimating the correct interfaces between fatty and fibroglandular tissue in the breast and their internal permittivity profiles. The level set strategy (which is an implicit representation of the shapes) frees us from topological restrictions when reconstructing an a priori arbitrary number of tumors and the often quite complicated interfaces between fatty and fibroglandular regions. The presented strategy is able to detect and, in most cases, characterize tumors whose sizes (diameters) are much smaller than the wavelengths of the electromagnetic waves that are used for illuminating the breast. We present numerical results for a 2-D model with two distinct tissue types (fatty and fibroglandular) in the interior of the breast (in addition to a possible tumor and the surrounding skin). Our results demonstrate the performance and potential of our scheme in various simulated but realistic situations.

Effect of lesion morphology on microwave signature in 2-D ultra-wideband breast imaging

This paper studies the possibility of distinguishing between benign and malignant masses by exploiting the morphology-dependent temporal and spectral characteristics of their microwave backscatter response in ultra-wideband breast cancer detection. The spiculated border profiles of 2-D breast masses are generated by modifying the baseline elliptical rings based upon the irregularity of their peripheries. Furthermore, the single- and multilayer lesion models are used to characterize a distinct mass region followed by a sharp transition to background, and a blurred mass border exhibiting a gradual transition to background, respectively. Subsequently, the complex natural resonances (CNRs) of the backscatter microwave signature can be derived from the late-time target response and reveal diagnostically useful information. The fractional sequence CLEAN algorithm is proposed to estimate the lesions' delay intervals and identify the late-time responses. Finally, it is shown through numerical examples that the locations of dominant CNRs are dependent on the lesion morphologies, where 2-D computational breast phantoms with single and multiple lesions are investigated. The analysis is of potential use for discrimination between benign and malignant lesions, where the former usually possesses a better-defined, more compact shape as opposed to the latter.

Measuring information gain for frequency-encoded super-resolution MRI

Super-resolution (SR)-based methods that implement multiple data sets related by spatial translations in the frequency-encoding (FE) direction have recently been proposed for resolution enhancement in MRI. This approach, however, was initially received with controversy. It was suggested that when the shifts are applied in the FE direction, no new information was acquired after the first image. Recent developments suggest, however, that shifting the object between image acquisitions can introduce new information to each data set. For this reason, SRMRI may be possible in the FE direction. In this article, we point out that the presence of new information in each acquisition is not sufficient for an SR algorithm to be practical. Indeed, there are situations where the amount of new information is relatively small and possibly not even measurable in the presence of noise. We explore the question of how much new information can be present in each acquisition for FE SRMRI. In particular, we investigate the extent to which the effect of the spatial shift - applied before the object is imaged - can be undone using simple image-processing techniques. Visual comparisons and numerical measures are used to characterize the amount of new information that is acquired in each data set. It is shown that since the amount of new information can be relatively small, each image can be approximated by applying simple signal-processing techniques to a single data set. Ultimately, our research suggests that little progress may be possible by using this approach to perform resolution enhancement in the FE direction.