Eric Clarkson - researchr alias

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Viewing Publication 1 - 27 from 27

2023

Approximating the idea observer on list mode data with comparison to CNN methodsDan Li, Eric Clarkson. miipop 2023: [doi]

2022

Performance of list mode Hotelling observer and comparison to a neural network observerDan Li, Eric Clarkson. miipop 2022: [doi]

2021

2020

Bayesian Fisher Information and Detection of a Small Change in a ParameterEric Clarkson. ciss 2020: 1-5 [doi]

Bayesian Fisher Information, Shannon Information, and ROC Analysis for Classification TasksEric Clarkson. acssc 2020: 1365-1369 [doi]

2016

Applying the J-optimal channelized quadratic observer to SPECT myocardial perfusion defect detectionMeredith K. Kupinski, Eric Clarkson, Michael Ghaly, Eric C. Frey. miipop 2016: 978708 [doi]

2009

Global Compartmental Pharmacokinetic Models for Spatiotemporal SPECT and PET ImagingEric Clarkson, Matthew A. Kupinski. siamis, 2(1):203-225, 2009. [doi]

2008

2004

Image-Quality Assessment in Optical TomographyMatthew A. Kupinski, Eric Clarkson. isbi 2004: 1471-1474

2003

Predicting Accuracy in Pose Estimation for Marker-based TrackingLarry S. Davis, Eric Clarkson, Jannick P. Rolland. ismar 2003: 28-35 [doi]

Ideal-Observer Performance under Signal and Background UncertaintySubok Park, Matthew A. Kupinski, Eric Clarkson, Harrison H. Barrett. ipmi 2003: 342-353 [doi]

2002

Methods for Designing Head-Tracking ProbesLarry S. Davis, Jannick P. Rolland, Rebecca Parsons, Eric Clarkson. jcis 2002: 498-502

Methods for Designing Head-Tracking ProbesLarry S. Davis, Jannick P. Rolland, Rebecca Parsons, Eric Clarkson. jcis 2002: 1357-1361

Objective Comparison of Quantitative Imaging Modalities Without the Use of a Gold StandardJohn W. Hoppin, Matthew A. Kupinski, George A. Kastis, Eric Clarkson, Harrison H. Barrett. tmi, 21(5):441-449, 2002.

2001

Chemical-shift Imaging Utilizing the Positional Shifts along the Readout Gradient DirectionMaria I. Altbach, Theodore P. Trouard, Rik Van de Walle, Rebecca J. Theilman, Eric Clarkson, Harrison H. Barrett, Arthur F. Gmitro. tmi, 20(11):1156-1166, 2001.

Comments on the Filtered Backprojection Algorithm, Range Conditions, and the Pseudoinverse SolutionMark A. Anastasio, Xiaochuan Pan, Eric Clarkson. tmi, 20(6):539-542, 2001.

Objective Comparison of Quantitative Imaging Modalities Without the Use of a Gold StandardJohn W. Hoppin, Matthew A. Kupinski, George A. Kastis, Eric Clarkson, Harrison H. Barrett. ipmi 2001: 12-23 [doi]

Estimability of Spatio-temporal Activation in fMRIAndre Lehovich, Harrison H. Barrett, Eric Clarkson, Arthur F. Gmitro. ipmi 2001: 259-271 [doi]

Nonlinear discriminant analysisHongbin Zhang, Eric Clarkson, Harrison H. Barrett. miip 2001: [doi]

Feature extraction method based on the ideal observerHongbin Zhang, Eric Clarkson, Harrison H. Barrett. miip 2001: [doi]

2000

Angular Channels in a Multidimensional Wavelet TransformEric Clarkson. siamma, 32(1):80-102, 2000. [doi]

A high resolution synthetic collimator for reconstructing 2D and 3D radiotracer distributionsD. W. Wilson, Harrison H. Barrett, Eric Clarkson. tmi, 19(5):412-422, 2000.

1998

A method for approximating the density of maximum-likelihood and maximum a posteriori estimates under a Gaussian noise modelCraig K. Abbey, Eric Clarkson, Harrison H. Barrett, Stefan P. Müller, Frank J. Rybicki. mia, 2(4):395-403, 1998. [doi]

1997

Approximate Distributions for Maximum Likelihood and Maximum a posteriori Estimates Under a Gaussain Noise ModelCraig K. Abbey, Eric Clarkson, Harrison H. Barrett, Stefan P. Müller, Frank J. Rybicki. ipmi 1997: 167-175

Bayesian Detection with Amplitude, Scale, Orientation and Position UncertaintyEric Clarkson, Harrison H. Barrett. ipmi 1997: 549-554

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