Ms. Tamara Sobers Profile

Tamara Sobers

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Proceedings Article | 29 March 2013 Paper

Optimal basis for real-time compression of ultrasound RF signals

Sharmin Kibria, Patrick Kelly, Tamara Sobers, Jai Gupta, Linda Gupta

Proceedings Volume 8675, 86751J (2013) https://doi.org/10.1117/12.2006830

KEYWORDS: Ultrasonography, Phased arrays, Fourier transforms, Analog electronics, Beam analyzers, Tissues, Data conversion, Matrices, Acoustics, Optical spheres

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Modern medical ultrasound machines produce enormous amounts of data, as much as several gigabytes/sec in some systems. The difficulties of generating, propagating and processing such large amounts of data have motivated recent research into means for compression of the radio frequency (rf) signals received at an ultrasound system’s analog front end. Most of this work has concentrated on the digitized data available after sampling and A/D conversion. We are interested in the possibility of compression implemented directly on the received analog signals, so we focus on efficient real-time representations for the rf signals comprising a single receive aperture. We first derive an expression for the (time and space) autocorrelation function of the set of signals received in a linear aperture. This is then used to find the autocorrelation’s eigenfunctions, which form an optimal basis for minimum mean-square error (mmse) compression of the aperture signal set. Computation of the coefficients of the signal set with respect to the basis amounts to calculation of Fourier Series coefficients for the received signal at each aperture element, with frequencies scaled by aperture position, followed by linear combinations of corresponding frequency components across the aperture. The combination weights at each frequency are determined by the eigenvectors of a matrix whose entries are averaged cross-spectral coefficients of the received signal set at that frequency. The autocorrelation decomposition and signal set coefficients are also used to compute a linear mmse beamformed estimate of the aperture center line.

Proceedings Article | 3 March 2012 Paper

Microwave radiometric signatures of temperature anomalies in tissue

Patrick Kelly, Tamara Sobers, Benjamin St. Peter, Paul Siqueira, Geoffrey Capraro

Proceedings Volume 8313, 831368 (2012) https://doi.org/10.1117/12.910785

KEYWORDS: Tissues, Waveguides, Associative arrays, Radiometry, Dielectrics, Blood, Skin, Temperature metrology, Microwave radiation, Detection and tracking algorithms

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Because of its ability to measure the temperature-dependent power of electromagnetic radiation emitted from tissue down to several centimeters beneath the skin, microwave radiometry has long been of interest as a means for identifying the internal tissue temperature anomalies that arise from abnormalities in physiological parameters such as metabolic and blood perfusion rates. However, the inherent lack of specificity and resolution in microwave radiometer measurements has limited the clinical usefulness of the technique. The idea underlying this work is to make use of information (assumed to be available from some other modality) about the tissue configuration in the volume of interest to study and improve the accuracy of anomaly detection and estimation from radiometric data. In particular, knowledge of the specific anatomy and the properties of the overall measurement system enable determination of the signatures of localized physiological abnormalities in the radiometry data. These signatures are used to investigate the accuracy with which the location of an anomaly can be determined from radiometric measurements. Algorithms based on matches to entries in a signature dictionary are developed for anomaly detection and estimation. The accuracy of anomaly identification is improved when the coupling of power from the body to the sensor is optimized. We describe the design of a radiometer waveguide having dielectric properties appropriate for biomedical applications.

Proceedings Article | 17 March 2011 Paper

Temperature anomaly detection and estimation using microwave radiometry and anatomical information

Patrick Kelly, Tamara Sobers, Benjamin St. Peter, Paul Siqueira, Geoffrey Capraro

Proceedings Volume 7961, 79614U (2011) https://doi.org/10.1117/12.878136

KEYWORDS: Temperature metrology, Tissues, Radiometry, Microwave radiometry, Antennas, Microwave radiation, Head, Waveguides, S band, Radio propagation

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Many medically significant conditions (e.g., ischemia, carcinoma and inflammation) involve localized anomalies in physiological parameters such as the metabolic and blood perfusion rates. These in turn lead to deviations from normal tissue temperature patterns. Microwave radiometry is a passive system for sensing the radiation that objects emit naturally in the microwave frequency band. Since the emitted power depends on temperature, and since radiation at low microwave frequencies can propagate through several centimeters of tissue, microwave radiometry has the potential to provide valuable information about subcutaneous anomalies. The radiometric temperature measurement for a tissue region can be modeled as the inner product of the temperature pattern and a weighting function that depends on tissue properties and the radiometer's antenna. In the absence of knowledge of the weighting functions, it can be difficult to extract specific information about tissue temperature patterns (or the underlying physiological parameters) from the measurements. In this paper, we consider a scenario in which microwave radiometry works in conjunction with another imaging modality (e.g., 3D-CT or MRI) that provides detailed anatomical information. This information is used along with sensor properties in electromagnetic simulation software to generate weighting functions. It also is used in bio-heat equations to generate nominal tissue temperature patterns. We then develop a hypothesis testing framework that makes use of the weighting functions, nominal temperature patterns, and maximum likelihood estimates to detect anomalies. Simulation results are presented to illustrate the proposed detection procedures. The design and performance of an S-band (2-4 GHz) radiometer, and some of the challenges in using such a radiometer for temperature measurements deep in tissue, are also discussed.

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