Dr. Alan H. Baydush Profile

Dr. Alan H. Baydush

Assistant Professor

SPIE Involvement:

Author

Publications (17)

Proceedings Article | 13 March 2007 Paper

Initial application of digital tomosynthesis to improve brachytherapy treatment planning

Alan Baydush, Mahta Mirzaei McKee, June King, Devon Godfrey

Proceedings Volume 6510, 65102F (2007) https://doi.org/10.1117/12.713845

KEYWORDS: Imaging systems, X-ray computed tomography, Visualization, Computed tomography, Data acquisition, Reconstruction algorithms, Bladder, Radiation oncology, X-ray imaging, X-rays

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Proceedings Article | 17 March 2006 Paper

Mass detection in mammographic ROIs using Watson filters

Swatee Singh, Alan Baydush, Brian Harrawood, Joseph Lo

Proceedings Volume 6146, 614603 (2006) https://doi.org/10.1117/12.653224

KEYWORDS: Performance modeling, Solid modeling, Visual process modeling, Tumor growth modeling, Databases, Image filtering, Digital mammography, Mammography, Breast cancer, Human vision and color perception

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Proceedings Article | 20 April 2005 Paper

Initial application of digital tomosynthesis with on-board imaging in radiation oncology

Alan Baydush, Devon Godfrey, Mark Oldham, James Dobbins

Proceedings Volume 5745, (2005) https://doi.org/10.1117/12.596245

KEYWORDS: Radiation oncology, Computed tomography, Sensors, Data acquisition, Tumors, Imaging systems, CT reconstruction, Visualization, Image processing, Radiotherapy

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Proceedings Article | 12 May 2004 Paper

Development and application of a segmentation routine in a mammographic mass CAD system

David Catarious, Alan Baydush, Carey Floyd

Proceedings Volume 5370, (2004) https://doi.org/10.1117/12.536177

KEYWORDS: Image segmentation, CAD systems, Databases, Feature extraction, Feature selection, Mammography, Computer aided diagnosis and therapy, Image filtering, Breast

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Proceedings Article | 5 June 2003 Paper

Bi-plane correlation imaging for improved detection of lung nodules

Ehsan Samei, David Catarious, Alan Baydush, Carey Floyd, Rene Vargas-Voracek

Proceedings Volume 5030, (2003) https://doi.org/10.1117/12.480478

KEYWORDS: Brain-machine interfaces, Computer aided design, Lung, Chest, Image processing, Lung cancer, Radiography, Computer aided diagnosis and therapy, X-rays, Signal detection

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Proceedings Article | 22 May 2003 Paper

Computer-aided detection of masses in mammography using a Laguerre-Gauss channelized hotelling observer

Alan Baydush, David Catarious, Carey Floyd

Proceedings Volume 5034, (2003) https://doi.org/10.1117/12.480070

KEYWORDS: Databases, Mammography, CAD systems, Computer aided diagnosis and therapy, Cancer, Data modeling, Medical imaging, Solid modeling, Statistical analysis, Breast cancer

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Proceedings Article | 15 May 2003 Paper

A mammographic mass CAD system incorporating features from shape, fractal, and channelized Hotelling observer measurements: preliminary results

David Catarious, Alan Baydush, Craig Abbey, Carey Floyd

Proceedings Volume 5032, (2003) https://doi.org/10.1117/12.480868

KEYWORDS: Fractal analysis, Mammography, CAD systems, Image filtering, Feature extraction, Databases, Digital mammography, Feature selection, Gaussian filters, Breast cancer

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Proceedings Article | 12 April 2002 Paper

Human-observer templates for detection of a simulated lesion in mammographic images

Craig Abbey, Miguel Eckstein, Steven Shimozaki, Alan Baydush, David Catarious, Carey Floyd

Proceedings Volume 4686, (2002) https://doi.org/10.1117/12.462683

KEYWORDS: Data modeling, Spatial frequencies, Mammography, Visualization, Signal detection, Composites, Diagnostics, Image processing, Databases, Digital mammography

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Proceedings Article | 3 July 2001 Paper

Initial development of a computer-aided diagnosis tool for solitary pulmonary nodules

David Catarious, Alan Baydush, Carey Floyd

Proceedings Volume 4322, (2001) https://doi.org/10.1117/12.431148

KEYWORDS: Fractal analysis, Computer aided diagnosis and therapy, Databases, Lung, CAD systems, Lung cancer, Chest imaging, Cancer, Artificial neural networks, Image segmentation

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Proceedings Article | 3 July 2001 Paper

Novel use of the Hotelling observer for computer-aided diagnosis of solitary pulmonary nodules

Alan Baydush, David Catarious

Proceedings Volume 4322, (2001) https://doi.org/10.1117/12.431085

KEYWORDS: Databases, Computer aided diagnosis and therapy, Medical imaging, Signal detection, Lung, Cancer, Visual process modeling, Image quality, Chest imaging, Artificial neural networks

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Proceedings Article | 6 June 2000 Paper

Improved image quality with Bayesian image processing in digital mammography

Alan Baydush, Carey Floyd

Proceedings Volume 3979, (2000) https://doi.org/10.1117/12.387740

KEYWORDS: Image processing, Digital mammography, Mammography, Image analysis, Digital imaging, Image quality, Calibration, Visualization, Sensors, Statistical analysis

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Proceedings Article | 21 May 1999 Paper

Comparison of contrast-to-noise ratios for Bayesian processing and grids in digital chest radiography

Alan Baydush, Wendy Gehm, Carey Floyd

Proceedings Volume 3661, (1999) https://doi.org/10.1117/12.348622

KEYWORDS: Image processing, Chest, Radiography, Lung, Image analysis, Chest imaging, Image resolution, Abdomen, X-rays, Error analysis

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Proceedings Article | 24 June 1998 Paper

Spatially varying scatter compensation for digital chest radiography

Alan Baydush, Carey Floyd

Proceedings Volume 3338, (1998) https://doi.org/10.1117/12.310971

KEYWORDS: Chest, Lung, Radiography, Image processing, Image quality, Image analysis, X-rays, Expectation maximization algorithms, Image resolution, Chest imaging

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Proceedings Article | 16 April 1996 Paper

Scatter reduction in mammography using statistical estimation techniques

Alan Baydush, Jacob Laading, Carey Floyd

Proceedings Volume 2710, (1996) https://doi.org/10.1117/12.237975

KEYWORDS: Mammography, Image processing, Visualization, Chest, Image quality standards, Radiography, Image resolution, Digital imaging, Image analysis, Statistical analysis

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Proceedings Article | 11 April 1996 Paper

Novel statistical analysis of two sources of digital chest radiographs

Jacob Laading, Valen Johnson, Alan Baydush, Carey Floyd

Proceedings Volume 2708, (1996) https://doi.org/10.1117/12.237825

KEYWORDS: Statistical analysis, Chest imaging, Data modeling, Image processing, Statistical modeling, Radiography, Chest, Medical imaging, Fourier transforms, Image resolution

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Statistical estimation techniques for medical images require well-founded models for the data formation and acquisition process. In our work, we attempt to quantify the appropriate empirical noise model for two alternative digital chest radiography modalities. In this study, we acquired image sets from the same clinical x-ray unit using photostimulable phosphor plates (PPP) and film/screen. The images were acquired in the range of 1-9 mR. The PPP data, at 1760 by 2140 pixels, were transferred directly to our workstations for analysis, and the films were digitized at 2048 by 2480 pixels (0.2 mm resolution for both modalities). 1024 by 1024 regions of interest (ROIs) without edge effects or artifacts were then extracted. Using Fourier transform methods, the noise power spectra were formed for all the images with smoothing applied near the axes to exclude frequency components due to beam profile, detector inhomogeneity and other structural noise. The noise power spectra were then integrated to find the variance at the exposure in question. This corresponds to an estimate of the non-structural variance. The data for all images obtained with one method were finally combined to form the variance function (variance as a function of the mean) for the modality. The data show that for the range of exposure considered, the PPP and digitized film modalities exhibit significant differences in noise structure. Subtle differences in the noise power spectra were seen. Of particular interest to our application, however, the variance function in the two cases was seen to differ in its functional form. The data from the photostimulable phosphor plates correspond well to a linear model (variance proportional to the mean) throughout most of the range investigated, whereas the digitized film variance function corresponds better to a higher-degree polynomial fit over the range considered. This study indicates that separate models may be warranted for different sources of digital chest radiographs and also suggests the type of assumption that, based on empirical findings, may be useful in such a framework.

Proceedings Article | 11 May 1994 Paper

Effect of maximum likelihood-median processing on the contrast-to-noise ratio in digital chest radiography

Alan Baydush, Carey Floyd

Proceedings Volume 2167, (1994) https://doi.org/10.1117/12.175093

KEYWORDS: Image processing, Chest, Radiography, Lung, Digital filtering, Image quality, Image enhancement, Image visualization, Image analysis, Photons

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Proceedings Article | 11 May 1994 Paper

Spatially varying scatter compensation for chest radiographs using a hybrid Madaline artificial neural network

Joseph Lo, Alan Baydush, Carey Floyd

Proceedings Volume 2167, (1994) https://doi.org/10.1117/12.175095

KEYWORDS: Image segmentation, Matrices, Neural networks, Convolution, Radiography, Chest, Lung, Artificial neural networks, Digital filtering, Point spread functions

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Showing 5 of 17 publications

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