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Matthew A. Kupinski
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2020 – today
- 2021
- [c10]Matthew A. Kupinski, Jiahua Fan:
Observer models utilizing compressed textures. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2021 - 2020
- [c9]Matthew A. Kupinski, Zachary Garrett, Jiahua Fan:
Observer-driven texture analysis in CT imaging. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 1131610
2010 – 2019
- 2019
- [j11]Yujia Chen
, Yang Lou, Kun Wang
, Matthew A. Kupinski, Mark A. Anastasio
:
Reconstruction-Aware Imaging System Ranking by Use of a Sparsity-Driven Numerical Observer Enabled by Variational Bayesian Inference. IEEE Trans. Medical Imaging 38(5): 1251-1262 (2019) - [i2]Yujia Chen, Yang Lou, Kun Wang, Matthew A. Kupinski, Mark A. Anastasio:
Reconstruction-Aware Imaging System Ranking by use of a Sparsity-Driven Numerical Observer Enabled by Variational Bayesian Inference. CoRR abs/1905.05820 (2019) - 2016
- [c8]Hsin-Wu Tseng, Jiahua Fan, Matthew A. Kupinski, William Balhorn, Darin R. Okerlund:
Quantitative image quality evaluation for cardiac CT reconstructions. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2016: 978716 - [e1]Craig K. Abbey, Matthew A. Kupinski:
Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, San Diego, California, United States, 27 February - 3 March 2016. SPIE Proceedings 9787, SPIE 2016, ISBN 9781510600225 [contents] - [i1]Christopher J. MacGahan, Matthew A. Kupinski, Nathan R. Hilton, Erik M. Brubaker, William C. Johnson:
Development of an Ideal Observer that Incorporates Nuisance Parameters and Processes List-Mode Data. CoRR abs/1602.01449 (2016)
2000 – 2009
- 2009
- [j10]Eric Clarkson, Matthew A. Kupinski:
Global Compartmental Pharmacokinetic Models for Spatiotemporal SPECT and PET Imaging. SIAM J. Imaging Sci. 2(1): 203-225 (2009) - 2008
- [j9]Eric Clarkson, Matthew A. Kupinski, Harrison H. Barrett, Lars R. Furenlid:
A Task-Based Approach to Adaptive and Multimodality Imaging. Proc. IEEE 96(3): 500-511 (2008) - [j8]Harrison H. Barrett, L. R. Furenlid, M. Freed, J. Y. Hesterman, Matthew A. Kupinski, Eric Clarkson, M. K. Whitaker:
Adaptive SPECT. IEEE Trans. Medical Imaging 27(6): 775-788 (2008) - [c7]L. R. Furenlid, J. W. Moore, M. Freed, Matthew A. Kupinski, Eric Clarkson, Z. Liu, D. W. Wilson, James M. Woolfenden, Harrison H. Barrett:
Adaptive small-animal SPECT/CT. ISBI 2008: 1407-1410 - 2004
- [j7]Darrin C. Edwards, Charles E. Metz, Matthew A. Kupinski:
Ideal observers and optimal ROC hypersurfaces in N-class classification. IEEE Trans. Medical Imaging 23(7): 891-895 (2004) - [c6]Matthew A. Kupinski, Eric Clarkson:
Image-Quality Assessment in Optical Tomography. ISBI 2004: 1471-1474 - 2003
- [j6]Matthew A. Kupinski:
Guest editor's introduction - Computing in optics. Comput. Sci. Eng. 5(6): 13-14 (2003) - [c5]Subok Park, Matthew A. Kupinski, Eric Clarkson, Harrison H. Barrett:
Ideal-Observer Performance under Signal and Background Uncertainty. IPMI 2003: 342-353 - 2002
- [j5]John W. Hoppin, Matthew A. Kupinski, George A. Kastis
, Eric Clarkson, Harrison H. Barrett:
Objective Comparison of Quantitative Imaging Modalities Without the Use of a Gold Standard. IEEE Trans. Medical Imaging 21(5): 441-449 (2002) - 2001
- [j4]Matthew A. Kupinski, Darrin C. Edwards, Maryellen L. Giger
, Charles E. Metz:
Ideal Observer Approximation Using Bayesian Classification Neural Networks. IEEE Trans. Medical Imaging 20(9): 886-899 (2001) - [c4]John W. Hoppin, Matthew A. Kupinski, George A. Kastis, Eric Clarkson, Harrison H. Barrett:
Objective Comparison of Quantitative Imaging Modalities Without the Use of a Gold Standard. IPMI 2001: 12-23 - [c3]Darrin C. Edwards, John Papaioannou, Yulei Jiang, Matthew A. Kupinski, Robert M. Nishikawa
:
Eliminating false-positive microcalcification clusters in a mammography CAD scheme using a Bayesian neural network. Medical Imaging: Image Processing 2001 - 2000
- [c2]Matthew A. Kupinski, Mark A. Anastasio, Maryellen Lissak Giger:
Multiobjective genetic optimization of diagnostic classifiers used in the computerized detection of mass lesions in mammography. Medical Imaging: Image Processing 2000
1990 – 1999
- 1999
- [j3]Matthew A. Kupinski, Mark A. Anastasio:
Multiobjective Genetic Optimization of Diagnostic Classifiers with Implications for Generating ROC Curves. IEEE Trans. Medical Imaging 18(8): 675-685 (1999) - 1998
- [j2]Matthew A. Kupinski, Maryellen L. Giger:
Automated Seeded Lesion Segmentation on Digital Mammograms. IEEE Trans. Medical Imaging 17(4): 510-517 (1998) - [j1]Mark A. Anastasio, Matthew A. Kupinski, Robert M. Nishikawa
:
Optimization and FROC Analysis of Rule-Based Detection Schemes Using a Multiobjective Approach. IEEE Trans. Medical Imaging 17(6): 1089-1093 (1998) - 1997
- [c1]Matthew A. Kupinski, Maryellen L. Giger:
Feature selection and classifiers for the computerized detection of mass lesions in digital mammography. ICNN 1997: 2460-2463
Coauthor Index
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