Biomedical subjects

Paul M Meaney

Publications and source records attributed to Paul M Meaney.

7 recordsLinked to original sources

PubMed2006

The multidimensional phase unwrapping integral and applications to microwave tomographical image reconstruction.

Spatial unwrapping of the phase component of time varying electromagnetic fields has important implications in a range of disciplines including synthetic aperture radar (SAR) interferometry, MRI, optical confocal microscopy, and microwave tomography. This paper presents a fundamental framework based on the phase unwrapping integral, especially in the complex case where phase singularities are enclosed within the closed path integral. With respect to the phase unwrapping required when utilized in Gauss-Newton iterative microwave image reconstruction, the concept of dynamic phase unwrapping is introduced where the singularity location varies as a function of the iteratively modified property distributions. Strategies for dynamic phase unwrapping in the microwave problem were developed and successfully tested in simulations and clinical experiments utilizing large, high contrast targets to validate the approach.

Algorithms↗

PubMed2004

Microwave image reconstruction from 3-D fields coupled to 2-D parameter estimation.

An efficient Gauss-Newton iterative imaging technique utilizing a three-dimensional (3-D) field solution coupled to a two-dimensional (2-D) parameter estimation scheme (3-D/2-D) is presented for microwave tomographic imaging in medical applications. While electromagnetic wave propagation is described fully by a 3-D vector field, a 3-D scalar model has been applied to improve the efficiency of the iterative reconstruction process with apparently limited reduction in accuracy. In addition, the image recovery has been restricted to 2-D but is generalizable to three dimensions. Image artifacts related primarily to 3-D effects are reduced when compared with results from an entirely two-dimensional inversion (2-D/2-D). Important advances in terms of improving algorithmic efficiency include use of a block solver for computing the field solutions and application of the dual mesh scheme and adjoint approach for Jacobian construction. Methods which enhance the image quality such as the log-magnitude/unwrapped phase minimization were also applied. Results obtained from synthetic measurement data show that the new 3-D/2-D algorithm consistently outperforms its 2-D/2-D counterpart in terms of reducing the effective imaging slice thickness in both permittivity and conductivity images over a range of inclusion sizes and background medium contrasts.

Algorithms↗

PubMed2004

Electromagnetic breast imaging: average tissue property values in women with negative clinical findings.

Representative data are provided for three electromagnetic breast imaging techniques-near-infrared spectroscopy, electrical impedance spectroscopy, and microwave imaging spectroscopy-to serve as potential benchmarks for future investigation. The breasts of 23 women without clinical or mammographic findings of disease were imaged in the coronal plane with nonionizing radiation of varying frequencies. Average electromagnetic property values were reconstructed at each frequency on the basis of computational models of light diffusion, current flow, and microwave propagation. Electromagnetic properties were correlated with subject characteristics and between techniques. Each technique yielded information on breast tissue features (eg, conductivity, permittivity, light scattering, and absorption) that had not previously all been measured in the same individuals.

Adult↗

PubMed2003

Comparisons of three alternative breast modalities in a common phantom imaging experiment.

Four model-based imaging systems are currently being developed for breast cancer detection at Dartmouth College. A potential advantage of multimodality imaging is the prospect of combining information collected from each system to provide a more complete diagnostic tool that covers the full range of the patient and pathology spectra. In this paper it is shown through common phantom experiments on three of these imaging systems that it was possible to correlate different types of image information to potentially improve the reliability of tumor detection. Imaging experiments were conducted with common phantoms which mimic both dielectric and optical properties of the human breast. Cross modality comparison was investigated through a statistical study based on the repeated data sets of reconstructed parameters for each modality. The system standard error between all methods was generally less than 10% and the correlation coefficient across modalities ranged from 0.68 to 0.91. Future work includes the minimization of bias (artifacts) on the periphery of electrical impedance spectroscopy images to improve cross modality correlation and implementation of the multimodality diagnosis for breast cancer detection.

Breast Neoplasms↗

PubMed2002

Pre-scaled two-parameter Gauss-Newton image reconstruction to reduce property recovery imbalance.

Gauss-Newton image reconstruction in microwave imaging can be formulated in terms of a single complex quantity, the wave number squared (k2), with the understanding that the relative permittivity and conductivity images can be extracted afterwards through a simple constitutive relationship. However, this approach ignores the fact that the magnitude of the average real and imaginary components can be considerably out of balance depending on the operating frequency and tissue characteristics which can inadvertently imbalance the process in favour of one parameter over the other. In an effort to achieve property recovery which is balanced, we introduce a pre-scaling procedure at the property update stage of the reconstruction. Utilization of this concept in conjunction with our two-step regularization process for both simulation and phantom experiments demonstrates that the penalty term weighting parameters for the optimal mean-squared property errors for the two recovered distributions (relative permittivity and conductivity) together with that yielding the lowest least-squared electric field error coincide only when the scaling is applied. The scheme provides a means for simultaneous optimization of the two permittivity and conductivity images.

Algorithms↗

PubMed2002

Fundamental limitations of noninvasive temperature imaging by means of ultrasound echo strain estimation.

Ultrasonic estimation of temperature-induced echo strain has been suggested as a means of predicting the location of thermal lesions formed by focused ultrasound (US) surgery before treatment. Preliminary investigations of this technique have produced optimistic results because they were carried out with rubber phantoms and used room temperature, rather than body temperature, as the baseline. The objective of the present study was to determine, through modelling, the likely feasibility of using ultrasonic temperature imaging to detect and localise the focal region of the heating beam for a medium with a realistic temperature-dependence of sound speed subjected to a realistic temperature rise. We determined the minimum ultrasonic signal-to-noise ratio (SNR) required to visualise the heated region for liver of varying fat content. Due to the small (0.5%) change in sound speed at the focus, the threshold SNR for normal liver (low fat content) was found to be at least 20 dB. This implies that temperature imaging in this tissue type will only be feasible if the effects of electronic noise can be minimised and if other sources of noise, such as cardiac-induced motion, do not substantially reduce the visibility of the focal region. For liver of intermediate fat content, the heated region could not be visualised even when the echo data were noise-free. Tissues with a very high fat content are likely to represent the most favourable conditions for ultrasonic temperature imaging.

Body Temperature↗

PubMed2002

Quantification of 3-D field effects during 2-D microwave imaging.

Two-dimensional (2-D) approaches to microwave imaging have dominated the research landscape primarily due to the moderate levels of measurement data, data-acquisition time, and computational costs required. Three-dimensional (3-D) approaches have been investigated in simulation, phantom, and animal experiments. While 3-D approaches are certainly important in terms of the potential to improve image quality, their associated costs are significant at this time. In addition, benchmarks are needed to evaluate these new generation systems as more 3-D methods begin to appear. In this paper, we present a systematic series of experiments which assess the capability of our 2-D system to image classical 3-D geometries. We demonstrate where current methods suffer from 3-D effects but also identify situations where they remain quite useful. Comparisons between reconstructions utilizing phantom measurements and simulated 3-D data are also shown to validate the results. These findings suggest that for certain biomedical applications, 2-D approaches remain quite attractive.

Computer Simulation↗