Ms. Olga Pawluczyk Profile

Olga Pawluczyk

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Publications (5)

Proceedings Article | 13 February 2009 Paper

High-performance dispersive Raman and absorption spectroscopy as tools for drug identification

Olga Pawluczyk, Sam Andrey, Paul Nogas, Andrew Roy, Romuald Pawluczyk

Proceedings Volume 7182, 71820M (2009) https://doi.org/10.1117/12.809112

KEYWORDS: Raman spectroscopy, Spectroscopy, Magnesium, Tablets, Statistical analysis, Sodium, Medicine, Iron, Oxides, Titanium dioxide

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Proceedings Article | 14 February 2007 Paper

Spectral imaging of microscopic samples with high-performance CCD array-based spectrometer

Olga Pawluczyk, Romuald Pawluczyk

Proceedings Volume 6443, 64430G (2007) https://doi.org/10.1117/12.702866

KEYWORDS: Spectroscopy, Microscopes, Hyperspectral imaging, Luminescence, Imaging systems, Absorption, Spectral resolution, Imaging spectroscopy, Diffraction gratings, Sensors

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Proceedings Article | 13 October 2005 Paper

High-performance broad-band spectroscopy for breast cancer risk assessment

Olga Pawluczyk, Kristina Blackmore, Samantha Dick, Lothar Lilge

Proceedings Volume 5969, 59691M (2005) https://doi.org/10.1117/12.629075

KEYWORDS: Breast, Breast cancer, Tissues, Spectroscopy, Sensors, Spectrometers, Signal to noise ratio, Tissue optics, Mammography, Signal attenuation

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Proceedings Article | 9 December 2004 Paper

Applications of multichannel imaging spectrometer

Olga Pawluczyk, Romuald Pawluczyk

Proceedings Volume 5578, (2004) https://doi.org/10.1117/12.567422

KEYWORDS: Spectroscopy, Optical fibers, Optical design, Imaging systems, Diffraction gratings, Spectral resolution, Detector arrays, Holography, Multichannel imaging systems, Spectrometer engineering

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Proceedings Article | 25 April 2000 Paper

Estimation of volumetric breast density for breast cancer risk prediction

Olga Pawluczyk, Martin Yaffe, Norman Boyd, Roberta Jong

Proceedings Volume 3977, (2000) https://doi.org/10.1117/12.384495

KEYWORDS: Breast, Breast cancer, Mammography, Tissues, Calibration, X-rays, Polymethylmethacrylate, Image processing, Nonuniformity corrections, Absorbance

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Mammographic density (MD) has been shown to be a strong risk predictor for breast cancer. Compared to subjective assessment by a radiologist, computer-aided analysis of digitized mammograms provides a quantitative and more reproducible method for assessing breast density. However, the current methods of estimating breast density based on the area of bright signal in a mammogram do not reflect the true, volumetric quantity of dense tissue in the breast. A computerized method to estimate the amount of radiographically dense tissue in the overall volume of the breast has been developed to provide an automatic, user-independent tool for breast cancer risk assessment. The procedure for volumetric density estimation consists of first correcting the image for inhomogeneity, then performing a volume density calculation. First, optical sensitometry is used to convert all images to the logarithm of relative exposure (LRE), in order to simplify the image correction operations. The field non-uniformity correction, which takes into account heel effect, inverse square law, path obliquity and intrinsic field and grid non- uniformity is obtained by imaging a spherical section PMMA phantom. The processed LRE image of the phantom is then used as a correction offset for actual mammograms. From information about the thickness and placement of the breast, as well as the parameters of a breast-like calibration step wedge placed in the mammogram, MD of the breast is calculated. Post processing and a simple calibration phantom enable user- independent, reliable and repeatable volumetric estimation of density in breast-equivalent phantoms. Initial results obtained on known density phantoms show the estimation to vary less than 5% in MD from the actual value. This can be compared to estimated mammographic density differences of 30% between the true and non-corrected values. Since a more simplistic breast density measurement based on the projected area has been shown to be a strong indicator of breast cancer risk (RR equals 4), it is believed that the current volumetric technique will provide an even better indicator. Such an indicator can be used in determination of the method and frequency of breast cancer screening, and might prove useful in measuring the effect of intervention measures such as drug therapy or dietary change on breast cancer risk.

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