Dr. Matthew A. Kupinski Profile

Dr. Matthew A. Kupinski

Professor at Wyant College of Optical Sciences

SPIE Involvement:

Equity, Diversity and Inclusion Committee | Conference Program Committee | Editorial Board Member: Journal of Medical Imaging | Author | Editor

Publications (51)

SPIE Journal Paper | 23 June 2022 Open Access

Fifty years of SPIE Medical Imaging proceedings papers

Robert Nishikawa, Christoph Hoeschen, Anant Madabhushi, Kyle Myers, Thomas Deserno, Elizabeth Krupinski, Ronald Summers, Claudia Mello-Thoms, Matthew Kupinski, Jeffrey Siewerdsen

JMI, Vol. 9, Issue S1, 012207, (June 2022) https://doi.org/10.1117/12.10.1117/1.JMI.9.S1.012207

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Proceedings Article | 4 April 2022 Poster + Paper

Simulations and analysis of fluorescence effects in semiconductor x-ray and gamma-ray detectors

Kelsea Cronin, Matthew Kupinski, H. Bradford Barber, Lars Furenlid

Proceedings Volume 12031, 120314P (2022) https://doi.org/10.1117/12.2610686

KEYWORDS: Sensors, Luminescence, Semiconductors, X-ray fluorescence spectroscopy, Electrodes, Signal detection, Monte Carlo methods, X-rays, Photons, Crystals

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Proceedings Article | 4 April 2022 Poster + Paper

A read-out strategy for high-resolution large-area SiPM-based modular gamma-ray cameras

Maria Ruiz-Gonzalez, Robert Richards, Kimberly Doty, Phillip Kuo, Matthew Kupinski, Lars Furenlid, Michael King

Proceedings Volume 12031, 120314K (2022) https://doi.org/10.1117/12.2610069

KEYWORDS: Cameras, Signal processing, Field programmable gate arrays, Electronics, Clocks, Gamma radiation, Modulators, Scintillation, Spatial resolution, Sensors

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Proceedings Article | 4 April 2022 Poster + Paper

Fisher information comparison between a monolithic and a fiber-optic light guide in a modular gamma camera

Kimberly Doty, Matthew Kupinski, R. Garrett Richards, Maria Ruiz-Gonzalez, Michael King, Phillip Kuo, Lars Furenlid

Proceedings Volume 12031, 120313E (2022) https://doi.org/10.1117/12.2611834

KEYWORDS: Refraction, Photon transport, Crystals, Single photon emission computed tomography, Fiber optics, Sensors, Spatial resolution, Cameras, Scintillation

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Proceedings Article | 21 March 2022 Presentation

Observer performance in multi-technology imaging

Matthew Kupinski, Eric Clarkson, Kelsea Cronin, James Woolfenden, John Humm, Lars Furenlid

Proceedings Volume PC12035, PC1203504 (2022) https://doi.org/10.1117/12.2613085

KEYWORDS: Sensors, Imaging systems, Spatial resolution, Single photon emission computed tomography, Tomography, Positron emission tomography, Nuclear medicine, Heart, Cameras

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Proceedings Article | 15 February 2021 Presentation + Paper

Observer models utilizing compressed textures

Matthew Kupinski, Jiahua Fan

Proceedings Volume 11599, 115990I (2021) https://doi.org/10.1117/12.2581363

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Proceedings Article | 16 March 2020 Paper

Observer-driven texture analysis in CT imaging

Matthew Kupinski, Zachary Garrett, Jiahua Fan

Proceedings Volume 11316, 1131610 (2020) https://doi.org/10.1117/12.2549042

KEYWORDS: Signal detection, Computed tomography, Image analysis, Medical imaging, Statistical analysis, Image quality

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Proceedings Article | 6 July 2018 Open Access

Terrestrial exoplanet coronagraph image quality polarization aberrations in Habex

J. Breckinridge, M. Kupinski, J. Davis, B. Daugherty, R. Chipman

Proceedings Volume 10698, 106981D (2018) https://doi.org/10.1117/12.2311880

KEYWORDS: Mirrors, Coronagraphy, Exoplanets, Polarization, Dielectric polarization, Telescopes, Wavefronts, Space telescopes, Image quality, Metals

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Direct imaging and spectroscopy of terrestrial exoplanets requires the control of vector electromagnetic fields to approximately one part in ten to the fifth over a few milliarc second FOV to achieve the necessary 10^-10 intensity contrast levels. Observations using space telescopes are necessary to achieve these levels of diffracted and scattered light control. The highly reflecting metal mirrors and their coatings needed to image these very faint exoplanets introduce polarization into the wavefront, which, in turn affects image quality and reduces exoplanet yield unless corrected. To identify and create the technologies and the electro-optical/mechanical-spacecraft systems models that will achieve these levels, NASA is currently developing two mission concepts, each with their own hardware vision. These are: The Habex, a habitable planet explorer and the LUVOIR, a Large Ultra-Violet Optical-Infrared space telescope system. This paper reports the results of polarization ray-tracing the HabEx detailed optical prescription provided by the project to the authors in the fall of 2017. Diattenuation and retardance across both the exit pupil associated with the occulting mask and the exit pupil associated with the coronagraph image plane are given as well as the corresponding Jones pupil matrices. These are calculated assuming isotropic coatings on all mirrors. Analysis and physical measurements indicates that the specification of the primary mirror for exoplanet coronagraphs will need to include a constraint on spatially varying polarization reflectivity (anisotropic coatings). The Jones exit-pupil phase terms, phi XX and phi YY just before the occulting mask differ in shape and are displaced one from the other by about 10 milli-waves. This shows that A/O, which corrects for geometric path differences, cannot completely correct for wavefront errors introduced by polarization for this particular prescription for HabEx. We suggest that these differences may be corrected by adjusting the opto-mechanical design to change angles of incidence on mirrors and corrected by adjusting the design of the dielectric coatings on the highly-reflecting mirror surfaces. Super-posing the phase of XX onto the phase of YY and then correcting using A/O will assure maximum power transmittance through the system and best contrast. These aspects require further investigation.

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SPIE Journal Paper | 21 November 2017 Open Access

Assessing computed tomography image quality for combined detection and estimation tasks

Hsin-Wu Tseng, Jiahua Fan, Matthew Kupinski

JMI, Vol. 4, Issue 04, 045503, (November 2017) https://doi.org/10.1117/12.10.1117/1.JMI.4.4.045503

KEYWORDS: Image quality, Computed tomography, Infrared imaging, Reconstruction algorithms, Signal detection, Fluctuations and noise, CT reconstruction, Medical imaging, Imaging systems, Statistical analysis

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Proceedings Article | 10 March 2017 Paper

Task-based data-acquisition optimization for sparse image reconstruction systems

Yujia Chen, Yang Lou, Matthew Kupinski, Mark Anastasio

Proceedings Volume 10136, 101360Z (2017) https://doi.org/10.1117/12.2255536

KEYWORDS: Image restoration, Systems modeling, Imaging systems, Magnetic resonance imaging, Reconstruction algorithms, Information operations, Statistical modeling, Compressed sensing, Stochastic processes, Bayesian inference, Signal detection, Data acquisition, Statistical analysis

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SPIE Journal Paper | 28 July 2016

Design of a practical model-observer-based image quality assessment method for x-ray computed tomography imaging systems

Hsin-Wu Tseng, Jiahua Fan, Matthew Kupinski

JMI, Vol. 3, Issue 03, 035503, (July 2016) https://doi.org/10.1117/12.10.1117/1.JMI.3.3.035503

KEYWORDS: Image quality, Signal detection, Statistical analysis, Systems modeling, X-ray computed tomography, Imaging systems, Data modeling, Fluctuations and noise, Matrices, Computed tomography

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Proceedings Article | 24 March 2016 Paper

Quantitative image quality evaluation for cardiac CT reconstructions

Hsin-Wu Tseng, Jiahua Fan, Matthew Kupinski, William Balhorn, Darin Okerlund

Proceedings Volume 9787, 978716 (2016) https://doi.org/10.1117/12.2208341

KEYWORDS: Computed tomography, Image quality, Reconstruction algorithms, Heart, Image processing, CT reconstruction, Temporal resolution, Electrocardiography, X-ray computed tomography, Error analysis, Motion estimation

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Proceedings Article | 27 August 2015 Paper

Optimization of an adaptive SPECT system with the scanning linear estimator

Nasrin Ghanbari, Eric Clarkson, Matthew Kupinski, Xin Li

Proceedings Volume 9594, 95940A (2015) https://doi.org/10.1117/12.2195782

KEYWORDS: Imaging systems, Single photon emission computed tomography, Monte Carlo methods, Error analysis, Interference (communication), Image quality, Sensors, Photons, Computing systems, Image analysis

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Proceedings Article | 17 March 2015 Paper

Sparsity-driven ideal observer for computed medical imaging systems

Kun Wang, Yang Lou, Matthew Kupinski, Mark Anastasio

Proceedings Volume 9416, 94161C (2015) https://doi.org/10.1117/12.2082316

KEYWORDS: Information operations, Imaging systems, Statistical analysis, Computing systems, Medical imaging, Statistical modeling, Data acquisition, Bayesian inference, Interference (communication), Magnetic resonance imaging

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Proceedings Article | 17 March 2015 Paper

Using the Wiener estimator to determine optimal imaging parameters in a synthetic-collimator SPECT system used for small animal imaging

Alexander Lin, Lindsay Johnson, Sepideh Shokouhi, Todd Peterson, Matthew Kupinski

Proceedings Volume 9416, 94160L (2015) https://doi.org/10.1117/12.2082971

KEYWORDS: Sensors, Brain, Imaging systems, Single photon emission computed tomography, Multiplexing, Germanium, Silicon, Image segmentation, Preclinical imaging, Image sensors

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Proceedings Article | 17 March 2015 Paper

Combination of detection and estimation tasks using channelized scanning linear observer for CT imaging systems

Hsin-Wu Tseng, Jiahua Fan, Matthew Kupinski

Proceedings Volume 9416, 94160H (2015) https://doi.org/10.1117/12.2081035

KEYWORDS: Infrared imaging, Image quality, Computed tomography, Reconstruction algorithms, Head, Signal detection, Imaging systems, Medical imaging, Medicine, Detection and tracking algorithms

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Proceedings Article | 5 March 2015 Paper

Application of maximum-likelihood estimation in optical coherence tomography for nanometer-class thickness estimation

Jinxin Huang, Qun Yuan, Patrice Tankam, Eric Clarkson, Matthew Kupinski, Holly Hindman, James Aquavella, Jannick Rolland

Proceedings Volume 9315, 93150F (2015) https://doi.org/10.1117/12.2083160

KEYWORDS: Optical coherence tomography, Point spread functions, Refractive index, Mirrors, Coating, Eye, Interfaces, Biological research, Statistical analysis, Cameras

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Proceedings Article | 20 October 2014 Paper

Molecular imaging in the College of Optical Sciences: an overview of two decades of instrumentation development

Lars Furenlid, Harrison Barrett, H. Bradford Barber, Eric Clarkson, Matthew Kupinski, Zhonglin Liu, Gail Stevenson, James Woolfenden

Proceedings Volume 9186, 91860J (2014) https://doi.org/10.1117/12.2064808

KEYWORDS: Imaging systems, Sensors, Cameras, Single photon emission computed tomography, Gamma radiation, Computing systems, Tomography, Collimators, Positron emission tomography, Electronics

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Proceedings Article | 12 September 2014 Paper

Fabrication of the pinhole aperture for AdaptiSPECT

Cécile Chaix, Stephen Kovalsky, Matthew Kupinski, Harrison Barrett, Lars Furenlid

Proceedings Volume 9214, 921408 (2014) https://doi.org/10.1117/12.2065907

KEYWORDS: Sensors, Camera shutters, Manufacturing, Imaging systems, Collimators, Tungsten, Additive manufacturing, Light emitting diodes, Switches, Single photon emission computed tomography

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SPIE Journal Paper | 18 July 2014

Diagnostic potential of multimodal imaging of ovarian tissue using optical coherence tomography and second-harmonic generation microscopy

Weston Welge, Andrew DeMarco, Jennifer Watson, Photini Rice, Jennifer Barton, Matthew Kupinski

JMI, Vol. 1, Issue 02, 025501, (July 2014) https://doi.org/10.1117/12.10.1117/1.JMI.1.2.025501

KEYWORDS: Optical coherence tomography, Second-harmonic generation, Tissues, Ovarian cancer, Diagnostics, Tissue optics, Ovary, Televisions, Multimodal imaging, Collagen

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Proceedings Article | 11 March 2014 Paper

Design of a practical model-observer-based image quality assessment method for CT imaging systems

Hsin-Wu Tseng, Jiahua Fan, Guangzhi Cao, Matthew Kupinski, Paavana Sainath

Proceedings Volume 9037, 90370O (2014) https://doi.org/10.1117/12.2042681

KEYWORDS: Computed tomography, Image quality, Imaging systems, Reconstruction algorithms, Statistical analysis, Signal to noise ratio, Matrices, Data analysis, Medical imaging, Systems modeling

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Proceedings Article | 4 March 2014 Paper

Simultaneous measurement of lipid and aqueous layers of tear film using optical coherence tomography and statistical decision theory

Jinxin Huang, Eric Clarkson, Matthew Kupinski, Jannick Rolland

Proceedings Volume 8936, 89360A (2014) https://doi.org/10.1117/12.2041898

KEYWORDS: Optical coherence tomography, Mathematical modeling, Sensors, Computer simulations, Error analysis, Statistical analysis, Interfaces, Eye, Cameras, Point spread functions

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Proceedings Article | 4 March 2014 Paper

Objective assessment of multimodality optical coherence tomography and second-harmonic generation image quality of ex vivo mouse ovaries using human observers

Weston Welge, Andrew DeMarco, Jennifer Watson, Photini Rice, Jennifer Barton, Matthew Kupinski

Proceedings Volume 8936, 893609 (2014) https://doi.org/10.1117/12.2040520

KEYWORDS: Optical coherence tomography, Second-harmonic generation, Ovarian cancer, Tissues, Televisions, Ovary, Diagnostics, Video, Tissue optics, Collagen

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Proceedings Article | 26 September 2013 Paper

SmartCAM: an adaptive clinical SPECT camera

Christopher Dumas, Adam Bernstein, Alonzo Espinoza, Donovan Morgan, Kevin Lewis, Matt Nipper, Harrison Barrett, Matthew Kupinski, Lars Furenlid

Proceedings Volume 8853, 885307 (2013) https://doi.org/10.1117/12.2030090

KEYWORDS: Cameras, Single photon emission computed tomography, Imaging systems, Aluminum, Data acquisition, Gamma radiation, Image resolution, Computed tomography, Computing systems, Metals

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Proceedings Article | 28 March 2013 Paper

Study of the radiation dose reduction capability of a CT reconstruction algorithm: LCD performance assessment using mathematical model observers

Jiahua Fan, Hsin-Wu Tseng, Matthew Kupinski, Guangzhi Cao, Paavana Sainath, Jiang Hsieh

Proceedings Volume 8673, 86731Q (2013) https://doi.org/10.1117/12.2007307

KEYWORDS: Infrared imaging, X-ray computed tomography, Image quality, Mathematical modeling, Head, Reconstruction algorithms, Computed tomography, LCDs, Imaging systems, CT reconstruction

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Proceedings Article | 19 March 2013 Paper

Joint reconstruction of activity and attenuation map using LM SPECT emission data

Abhinav Jha, Eric Clarkson, Matthew Kupinski, Harrison Barrett

Proceedings Volume 8668, 86681W (2013) https://doi.org/10.1117/12.2008111

KEYWORDS: Signal attenuation, Single photon emission computed tomography, Expectation maximization algorithms, Reconstruction algorithms, Computed tomography, Data modeling, Gamma radiation, Compton scattering, Algorithm development, Data processing

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SPIE Journal Paper | 10 February 2012 Open Access

Effect of noise on modulation amplitude and phase in frequency-domain diffusive imaging

Dongyel Kang, Matthew Kupinski

JBO, Vol. 17, Issue 1, 016010, (February 2012) https://doi.org/10.1117/12.10.1117/1.JBO.17.1.016010

KEYWORDS: Modulation, Phase shift keying, Heterodyning, Signal to noise ratio, Monte Carlo methods, Homodyne detection, Image intensifiers, Imaging systems, Sensors, Biological research

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SPIE Journal Paper | 7 February 2012 Open Access

Noise characteristics of heterodyne/homodyne frequency-domain measurements

DongYel Kang, Matthew Kupinski

JBO, Vol. 17, Issue 1, 015002, (February 2012) https://doi.org/10.1117/12.10.1117/1.JBO.17.1.015002

KEYWORDS: Photons, Modulation, Microchannel plates, Charge-coupled devices, Homodyne detection, Signal to noise ratio, Heterodyning, Phase shift keying, Sensors, Imaging systems

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Proceedings Article | 27 February 2010 Paper

Evaluating segmentation algorithms for diffusion-weighted MR images: a task-based approach

Abhinav Jha, Matthew Kupinski, Jeffrey Rodríguez, Renu Stephen, Alison Stopeck

Proceedings Volume 7627, 76270L (2010) https://doi.org/10.1117/12.845515

KEYWORDS: Image segmentation, Expectation maximization algorithms, Error analysis, Diffusion, Magnetic resonance imaging, Image processing algorithms and systems, Signal to noise ratio, Image analysis, Medical imaging, Fuzzy logic

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Proceedings Article | 27 February 2010 Paper

Therapy operating characteristic (TOC) curves and their application to the evaluation of segmentation algorithms

Harrison Barrett, Donald Wilson, Matthew Kupinski, Kasarachi Aguwa, Lars Ewell, Robert Hunter, Stefan Müller

Proceedings Volume 7627, 76270Z (2010) https://doi.org/10.1117/12.844189

KEYWORDS: Image segmentation, Tumors, Radiotherapy, Reconstruction algorithms, Monte Carlo methods, Tissues, Prostate, Gold, Imaging systems, Prostate cancer

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Proceedings Article | 13 March 2009 Paper

Singular value decomposition of pinhole SPECT systems

Robin Palit, Matthew Kupinski, Harrison Barrett, Eric Clarkson, John Aarsvold, Lana Volokh, Yariv Grobshtein

Proceedings Volume 7263, 72631U (2009) https://doi.org/10.1117/12.813799

KEYWORDS: Imaging systems, Single photon emission computed tomography, Cameras, Sensors, Computing systems, Matrices, Scintillation, Data modeling, Systems modeling, Radiology

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Proceedings Article | 30 March 2007 Paper

Adaptive Hotelling discriminant functions

Arthur Brème, Matthew Kupinski, Eric Clarkson, Harrison Barrett

Proceedings Volume 6515, 65150T (2007) https://doi.org/10.1117/12.707804

KEYWORDS: Signal detection, Tumors, Statistical analysis, Imaging systems, Image filtering, Medical imaging, Tissues, Image analysis, Fourier transforms, Performance modeling

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Proceedings Article | 28 March 2007 Paper

A prototype instrument for adaptive SPECT imaging

Melanie Freed, Matthew Kupinski, Lars Furenlid, Harrison Barrett

Proceedings Volume 6510, 65100V (2007) https://doi.org/10.1117/12.708818

KEYWORDS: Sensors, Imaging systems, Control systems, Single photon emission computed tomography, Gamma radiation, Facial recognition systems, Prototyping, Tumors, Image resolution, Cameras

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Proceedings Article | 21 March 2007 Paper

Evaluation of hardware in a small-animal SPECT system using reconstructed images

Jacob Hesterman, Matthew Kupinski, Eric Clarkson, Donald Wilson, Harrison Barrett

Proceedings Volume 6515, 65151G (2007) https://doi.org/10.1117/12.709730

KEYWORDS: Imaging systems, Single photon emission computed tomography, Objectives, Signal detection, Image quality, Matrices, Multiplexing, Cameras, Quantitative analysis, Tomography

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Proceedings Article | 20 March 2007 Paper

Bias in Hotelling observer performance computed from finite data

Matthew Kupinski, Eric Clarkson, Jacob Hesterman

Proceedings Volume 6515, 65150S (2007) https://doi.org/10.1117/12.707800

KEYWORDS: Signal to noise ratio, Statistical analysis, Sensors, Imaging systems, Image analysis, Matrices, Medical imaging, Solids, Tumors, Image quality

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Proceedings Article | 17 March 2006 Paper

Performance of a channelized-ideal observer using Laguerre-Gauss channels for detecting a Gaussian signal at a known location in different lumpy backgrounds

Subok Park, Eric Clarkson, Harrison Barrett, Matthew Kupinski, Kyle Myers

Proceedings Volume 6146, 61460P (2006) https://doi.org/10.1117/12.653931

KEYWORDS: Signal detection, Monte Carlo methods, Medical imaging, Image quality, Imaging systems, Computer simulations, Statistical analysis, Signal to noise ratio, Quality measurement, Image classification

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Proceedings Article | 6 April 2005 Paper

Experimental task-based optimization of a four-camera variable-pinhole small-animal SPECT system

Jacob Hesterman, Matthew Kupinski, Lars Furenlid, Donald Wilson

Proceedings Volume 5749, (2005) https://doi.org/10.1117/12.594386

KEYWORDS: Imaging systems, Single photon emission computed tomography, Medical imaging, Systems modeling, Computer simulations, Optimization (mathematics), Gamma ray imaging, Optical spheres

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Proceedings Article | 6 April 2005 Paper

Efficiency of human and model observers for signal-detection tasks in non-Gaussian distributed lumpy backgrounds

Subok Park, Eric Clarkson, Matthew Kupinski, Harrison Barrett

Proceedings Volume 5749, (2005) https://doi.org/10.1117/12.592238

KEYWORDS: Signal detection, Imaging systems, Image processing, Statistical analysis, Systems modeling, Signal to noise ratio, Monte Carlo methods, Image quality, Medical imaging, Mathematical modeling

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Proceedings Article | 6 April 2005 Paper

Probabilistic foundations of the MRMC method

Harrison Barrett, Matthew Kupinski, Eric Clarkson

Proceedings Volume 5749, (2005) https://doi.org/10.1117/12.595685

KEYWORDS: Stochastic processes, Probability theory, Statistical analysis, Statistical modeling, Medical imaging, Radiology, Analytical research, Process modeling, Radio optics, Gamma ray imaging

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Current approaches to ROC analysis use the MRMC (multiple-reader, multiple-case) paradigm in which several readers read each case and their ratings are used to construct an estimate of the area under the ROC curve or some other ROC-related parameter. Standard practice is to decompose the parameter of interest according to a linear model into terms that depend in various ways on the readers, cases and modalities. It is assumed that the terms are statistically independent (or at least uncorrelated). Bootstrap methods are then used to estimate the variance of the estimate and the contributions from the individual terms in the assumed expansion. Though the methodological aspects of MRMC analysis have been studied in detail, the literature on the probabilistic basis of the individual terms is sparse. In particular, few papers state what probability law applies to each term and what underlying assumptions are needed for the assumed independence. This paper approaches the MRMC problem from a mechanistic perspective. For a single modality, three sources of randomness are included: the images, the reader skill and the reader uncertainty. The probability law on the parameter estimate is written in terms of three nested conditional probabilities, and random variables associated with this probability are referred to as triply stochastic. The triply stochastic probability is used to define the overall average of any ROC parameter as well as certain partial averages of utility in MRMC analysis. When this theory is applied to estimates of an ROC parameter for a single modality, it is shown that the variance of the estimate can be written as a sum of three terms, rather than the four that would be expected in MRMC analysis. The usual terms in MRMC expansions do not appear naturally in multiply-stochastic theory. A rigorous MRMC expansion can be constructed by adding and subtracting partial averages to the parameter of interest in a tautological manner. In this approach the parameter is decomposed into a sum of four random uncorrelated, zero-mean random variables, with each term clearly defined in terms of conditional probabilities. When the variance of the expansion is computed, however, numerous subtractions occur, and there is no apparent advantage to computing the variance term by term; the final result is the same as one gets from the triply stochastic decomposition, at least for the Wilcoxon estimator. No other nontrivial MRMC expansion appears to be possible.

Proceedings Article | 6 April 2005 Paper

A fast model of a multiple-pinhole SPECT imaging system

Kevin Gross, Matthew Kupinski, Jacob Hesterman

Proceedings Volume 5749, (2005) https://doi.org/10.1117/12.595605

KEYWORDS: Imaging systems, Sensors, Information operations, Systems modeling, Single photon emission computed tomography, Monte Carlo methods, 3D modeling, Cameras, Image processing, Computer simulations

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Proceedings Article | 6 April 2005 Paper

Extending the channelized Hotelling observer to account for signal uncertainty and estimation tasks

Matthew Kupinski, Eric Clarkson

Proceedings Volume 5749, (2005) https://doi.org/10.1117/12.595680

KEYWORDS: Signal detection, Imaging systems, Image quality, Quality measurement, Signal to noise ratio, Medical imaging, Image processing, Associative arrays, Statistical analysis, Channel projecting optics

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Proceedings Article | 4 May 2004 Paper

Efficient channels for the ideal observer

Subok Park, Matthew Kupinski, Eric Clarkson, Harrison Barrett

Proceedings Volume 5372, (2004) https://doi.org/10.1117/12.531614

KEYWORDS: Imaging systems, Signal detection, Californium, Monte Carlo methods, Image processing, Numerical analysis, Medical imaging, Performance modeling, Statistical analysis, Fourier transforms

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Proceedings Article | 22 May 2003 Paper

Optimizing a multiple-pinhole SPECT system using the ideal observer

Kevin Gross, Matthew Kupinski, Todd Peterson, Eric Clarkson

Proceedings Volume 5034, (2003) https://doi.org/10.1117/12.480336

KEYWORDS: Imaging systems, 3D modeling, Monte Carlo methods, Systems modeling, Sensors, Signal detection, Single photon emission computed tomography, 3D image processing, Image quality, Medical imaging

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Proceedings Article | 22 May 2003 Paper

Assessing the accuracy of estimates of the likelihood ratio

Eric Clarkson, Matthew Kupinski, John Hoppin

Proceedings Volume 5034, (2003) https://doi.org/10.1117/12.480339

KEYWORDS: Statistical analysis, Signal detection, Imaging systems, Error analysis, Monte Carlo methods, Sensors, Electronic filtering, Signal to noise ratio, Receivers, Detector arrays

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Proceedings Article | 22 May 2003 Paper

Evaluating estimation techniques in medical imaging without a gold standard: experimental validation

John Hoppin, Matthew Kupinski, Donald Wilson, Todd Peterson, Benjamin Gershman, George Kastis, Eric Clarkson, Lars Furenlid, Harrison Barrett

Proceedings Volume 5034, (2003) https://doi.org/10.1117/12.480330

KEYWORDS: Gold, Single photon emission computed tomography, Statistical analysis, Image quality standards, Imaging systems, Medical imaging, Standards development, Heart, Computed tomography, Analytical research

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Proceedings Article | 22 May 2003 Paper

Optimizing imaging hardware for estimation tasks

Matthew Kupinski, Eric Clarkson, Kevin Gross, John Hoppin

Proceedings Volume 5034, (2003) https://doi.org/10.1117/12.480337

KEYWORDS: Imaging systems, Signal detection, Medical imaging, Monte Carlo methods, Tumors, Image resolution, Systems modeling, Image quality, Interference (communication), Biomedical optics

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Proceedings Article | 12 April 2002 Paper

Matching statistical object models to real images

Matthew Kupinski, Eric Clakrson, Harrison Barrett

Proceedings Volume 4686, (2002) https://doi.org/10.1117/12.462690

KEYWORDS: Imaging systems, Systems modeling, Statistical analysis, Monte Carlo methods, Optimization (mathematics), Statistical modeling, Image quality, Sensors, Data modeling, Mathematical modeling

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Proceedings Article | 3 July 2001 Paper

Eliminating false-positive microcalcification clusters in a mammography CAD scheme using a Bayesian neural network

Darrin Edwards, John Papaioannou, Yulei Jiang, Matthew Kupinski, Robert Nishikawa

Proceedings Volume 4322, (2001) https://doi.org/10.1117/12.431089

KEYWORDS: Signal detection, Mammography, Computer aided diagnosis and therapy, Neural networks, Feature extraction, Electronic filtering, Analytical research, Databases, Artificial neural networks, Data modeling

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Proceedings Article | 6 June 2000 Paper

Multiobjective genetic optimization of diagnostic classifiers used in the computerized detection of mass lesions in mammography

Matthew Kupinski, Mark Anastasio, Maryellen Giger

Proceedings Volume 3979, (2000) https://doi.org/10.1117/12.387596

KEYWORDS: Mammography, Genetics, Genetic algorithms, Diagnostics, Classification systems, Receivers, Databases, Image classification, Image processing, Detection and tracking algorithms

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Proceedings Article | 14 April 2000 Paper

Estimation of linear observer templates in the presence of multi-peaked gaussian noise through 2AFC experiments

Darrin Edwards, Matthew Kupinski, Robert Nishikawa, Charles Metz

Proceedings Volume 3981, (2000) https://doi.org/10.1117/12.383094

KEYWORDS: Matrices, Statistical analysis, Interference (communication), Signal detection, Computer aided diagnosis and therapy, Medical imaging, Image quality, Error analysis, Solid modeling, Computer aided design

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Proceedings Article | 12 May 1995 Paper

Computerized detection of mammographic lesions: performance of artificial neural network with enhanced feature extraction

Matthew Kupinski, Maryellen Giger, Ping Lu, Zhimin Huo

Proceedings Volume 2434, (1995) https://doi.org/10.1117/12.208759

KEYWORDS: Artificial neural networks, Neural networks, Feature extraction, Mammography, Databases, Image enhancement, Receivers, Pattern recognition, Digital imaging, Breast cancer

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Showing 5 of 51 publications

Proceedings Volume Editor (4)

SPIE Conference Volume | 31 May 2017

Medical Imaging 2017: Image Perception, Observer Performance, and Technology Assessment

SPIE Conference Volume | 17 June 2016

Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment

SPIE Conference Volume | 27 April 2015

Medical Imaging 2015: Image Perception, Observer Performance, and Technology Assessment

SPIE Conference Volume | 11 April 2014

Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment

Conference Committee Involvement (20)