Related Literature

Applications of Objective Measures of Image Quality

  1. C.-J. Lee, M. A. Kupinski and L. Volokh, “Assessment of cardiac single-photon emission computed tomography performance using a scanning linear observer,” Medical Physics. 40(1)::011906, 2013. PMC3581138.
  2. A. K. Jha, M. A. Kupinski, J. J. Rodriguez, R. M. Stephen, A. T. Stopeck, “Task-based evaluation of segmentation algorithms for Diffusion-weighted MRI without using a gold-standard,” Physics in Medicine and Biology 57(13): 4425-4446, 2012. PMC3932666.
  3. D. Kang, and M. A. Kupinski, “Signal detectability in diffusive media using phased arrays in conjunction with detector arrays,” Optics Express 20;19(13):12261-74, 2011. PMID: 21716463.
  4. J. Y. Hesterman, M. A. Kupinski, E. Clarkson, and H. H. Barrett, “PMID:21716463–A signal-detection study”, Medical Physic, 34:3034-3044, 2007. PMC2471875.
  5. L. Caucci, H. H. Barrett, N. Devaney, and J. L. Rodriguez, “Application of the Hotelling and ideal observers to detection and localization of exoplanets”, Journal of the Optical Society of America A 24(12):B13-B24, 2007.  PMC2596684.
  6. M. A. Kupinski, J. W. Hoppin, J. Krasnow, S. Dahlberg, J. A. Leppo, M. A. King, E. Clarkson, and H. H. Barrett,“Comparing cardiac ejection fraction estimation algorithms without a gold standard”, Academic Radiology 31:329-337, 2006. PMC2464280.
  7. A. K. Sahu, A. Joshi, M. A. Kupinski, E. M. Sevick-Muraca, “Assessment of a fluorescence-enhanced optical imaging system using the Hotelling observer”, Optics Express 14:7642-7660, 2006. PMC2832206.
  8. L. Chen and H. H. Barrett, “Task-based lens design with application to digital mammography”, Journal of the Optical Society of America A, 1:148-167, 2005.  PMC1785332.
  9.  J. Rolland, J. O’Daniel, C. Akcay, T. DeLemos, K. S. Lee, K-L. Cheong, E. Clarkson, R. Chakrabarti, and R. Ferris, “Task-based optimization and performance assessment in optical coherence imaging”, Journal of the Optical Society of America A, 22:1132-1142, 2005. PMID:15984486.
  10. J. D. Sain and H. H. Barrett, “Performance evaluation of a modular gamma camera using a detectability index”, Journal of Nuclear Medicine, 44:58-66, 2003. PMID:12515877.

Objective Assessment of Image Quality

  1. L. Caucci and H. H. Barrett, “Objective assessment of image quality: V. Photon-counting detectors and list-mode data,”Journal of the Optical Society of America A 29(6):1003-16, 2012.  PMC3377176.
  2. E. Clarkson, M. A. Kupinski, H. H. Barrett, and L. Furenlid, “A task-based approach to adaptive and multimodality imaging”, Proceedings of IEEE, 96(3):500-511, 2008. PMC2597814.
  3. M. A. Kupinski, A. B. Watson, J. H. Siewerdsen, K. J. Myers, and M. Eckstein, “Image Quality”, Journal of the Optical Society of America A, 24(12):IQ1-IQ1, 2007.
  4. H. H. Barrett, K. J. Myers, N. Devaney, and C. Dainty,“Objective assessment of image quality: IV. Application to adaptive optics”, Journal of the Optical Society of America A, 23:3080-3105, 2006. PMC2596685.

Basic Image-Quality Theory

  1. H. H. Barrett, “Objective assessment of image quality: Effects of quantum noise and object variability“, JOSA A, 7:1266-1278, 1990. PMID:  2370589.
  2. H. H. Barrett, J. L. Denny, R. F. Wagner, and K. J. Myers, “Objective assessment of image quality. II. Fisher information, Fourier crosstalk, and figures of merit for task performance“, JOSA A, 12:834-852, 1995.  PMID:7730951.
  3. H. H. Barrett, C. K. Abbey, and E. Clarkson, “Objective assessment of image quality. III. ROC metrics, ideal observers, and likelihood-generating functions“, JOSA A, 15:1520-1535, 1998. PMID: 9612940.
  4. H. H. Barrett, T. Gooley, K. Girodias, J. Rolland, T. White, and J. Yao, “Linear discriminants and image quality“, Image and Vision Computing, 10(6):451-460, 1992.
  5. H. H. Barrett, J. L. Denny, H. C. Giffort, and C. K. Abbey, “Generalized NEQ: Fourier analysis where you would least expect to find it“, SPIE, 2708:41-52, 1996.
  6. Medical Imaging — The Assessment of Image Quality. ICRU Report 54. International Commission on Radiation Units and Measurements. Bethesda MD (8 April 1996).
  7. R.F. Wagner and D.G. Brown, “Unified SNR analysis of medical imaging systems.” Phys. Med. Biol. (1985) vol 30, 489-518.
  8. D. W. Wilson, and H. H. Barrett, “Decomposition of images and objects into measurement and null components“, Optics Express, 2:254-260, 1998. PMID:  19377608.

Observer Models

  1. C. K. Abbey, and H. H. Barrett, “Human- and model-observer performance in ramp-spectrum noise: effects of regularization and object variability“, JOSA A. 18:473-488, 2001. PMC2943344.
  2. H. H. Barrett, J. Yao, J. P. Rolland, and K. J. Myers, “Model observers for assessment of image quality“, Proc. Natl. Acad. Sci., 90:9758-9765, 1993.
  3. J. P. Rolland, H. H. Barrett, and G. W. Seeley, “Ideal versus human observer for long-tailed point spread functions: does deconvolution help?“, Phys. Med. Biol. 36:1091-1109, 1991.  PMID: 1924544.
  4. C. K. Abbey, H. H. Barrett, and D. W. Wilson, “Observer signal-to-noise ratios for the ML-EM algorithm”, SPIE Vol 2712:47-58, 1996. PMC2943373.
  5. J. P. Rolland, and H. H. Barrett, “Effect of random background inhomogeneity on observer detection performance”, JOSA A, 9:649-658, 1992.  PMID: 1588452.
  6. D. Kang and M. A. Kupinski, “A new figure of merit for frequency-domain diffusive imaging,” Optics Letters 38(2): 235-7, 2013.
  7. E. Clarkson, “Asymptotic ideal observers and surrogate figures of merit for signal detection with list mode data,” Journal of the Optical Society of America A, 29(10): 2204-2216, 2012.  PMC3967985.
  8. E. Clarkson and F. Shen, “Fisher information and surrogate figures of merit for task-based assessment of image quality,”Journal of the Optical Society of America A, 27(10), 2313-2316, 2010. PMC2963440.
  9. S. Park and E. Clarkson, “Efficient estimation of ideal-observer performance in classification tasks involving complex backgrounds.” Journal of the Optical Society of America A, 26, B59-B71, 2009. PMC2909882.
  10. L. Caucci, H. H. Barrett, and J. J. Rodriguez, “Spatio-temporal Hotelling observer for signal detection from image sequences,“Optics Express 17,10946-10958, 2009. PMC2859675.
  11. M. K. Whitaker, E. Clarkson, and H. H. Barrett, “Estimating random signal parameters from noisy images with nuisance parameters: linear and scanning-linear methods”, Optics Express, 16(11):8150-8173, 2008. PMC2577032.
  12. S. Park, H. H. Barrett, E. Clarkson, M. A. Kupinski, and K. J. Myers, “Channelized-ideal observer using Laguerre-Gauss channels in detection tasks involving non-Gaussian distributed lumpy backgrounds and Gaussian signal”, Journal of the Optical Society of America A, 24(12):B136-B150, 2007.  PMC2655642.
  13. S. Park, E. Clarkson, M. A. Kupinski, and H. H. Barrett, “Efficiency of the human observer detecting random signals in random backgrounds”, Journal of the Optical Society of America A, 22(1):3-16, 2005. PMC2464287.
  14. S. Park, M. A. Kupinski, E. Clarkson, H. H. Barrett “Ideal-observer performance under signal and background uncertainty,” Lecture Notes in Computer Science. 2732, 342-353, 2003.
  15. A. R. Pineda, and H. H. Barrett, “Figures of merit for digital radiography. I. Flat background and deterministic blurring”, Medical Physics,31:348-358, 2004.
  16. A. R. Pineda, and H. H. Barrett, “Figures of merit for digital radiography. II. Finite number of secondaries, structured and random backgrounds”, Medical Physics, 31:359-367, 2004.
  17. M. A. Kupinski, J. W. Hoppin, E. Clarkson, and H. H. Barrett, “Ideal-observer computation in medical imaging with use of Markov-chain Monte Carlo”, Journal of the Optical Society of America A, 20:430-438, 2003.
  18. J. W. Hoppin, D. W. Wilson, T. E. Peterson, M. A. Kupinski, G. A. Kastis, E. Clarkson, L R. Furenlid, and H. H. Barrett, “Evaluating estimation techniques in medical imaging without a gold standard: experimental validation”, Proceedings of SPIE, 5034:230-237, 2003.
  19. M. A. Kupinski, E. Clarkson, K. Gross, J. W. Hoppin, and H. H. Barrett, “Optimizing imaging hardware for estimation tasks”, Proceedings of SPIE, 5034:309-313, 2003.
  20. B. D. Gallas and H. H. Barrett, “Validating the use of channels to estimate the ideal linear observer”, Journal of the Optical Society of America A, 20(9):1725-1738, 2003. PMID: 12968645

ROC

  1. C. E. Metz, “Basic principles of ROC Analysis.” Seminars in Nuclear Medicine 8(4):283-298, 1978. PMID: 112681.
  2. C. E. Metz, “ROC methodology in Radiologic imaging.” Investigative Radiology 21(9):720-733, 1986. PMID: 3095258.
  3. C. E. Metz, “Some practical issues of experimental design and data analysis in radiological ROC studies,” Invest Radiol., 24(3):234-245, 1989.  PMID: 2753640.
  4. R.F. Wagner, S.V. Beiden, C.E. Metz, “Continuous versus Categorical Data for ROC Analysis: Some Quantitative Considerations.” Acad Radiol., 8:328-334, 2001.  PMID: 11293781.
  5. S.V. Beiden, R.F. Wagner, G. Campbell, “Components-of-variance Models and Multiple-Bootstrap Experiments: An alternative method for random-effects, receiver operating characteristic analysis.” Acad Radiol 7(5): 341-349, 2000. PMID: 10803614.
  6. E. Clarkson, J. L. Denny and L. Shepp, “ROC and the bounds on tail probabilities via theorems of Dubins and F. Riesz,” Annals of Applied Probability 19(1):467-476, 2009. PMC2828638.
  7. E. Clarkson, “Estimation receiver operating characteristic curve and ideal observers for combined detection/estimation tasks”,Journal of the Optical Society of America A, 24(12):B91-B98, 2007. PMC2575755.
  8. E. Clarkson, M. A. Kupinski, H. H. Barrett, “A probabilistic model for the MRMC method, part 1: Theoretical development,”Academic Radiology. 13(11):1410-1421, 2006.  PMC2844793.
  9. M. A. Kupinski, E. Clarkson, and H. H. Barrett, “A probabilistic model for the MRMC method. Part 2: Validation and applications”, Academic Radiolology, 13(11):1422-1430, 2006. PMC2077079.