Observer Models as a Surrogate to Perception Experiments
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[1] Craig K. Abbey,et al. Derivation of an Observer Model Adapted to Irregular Signals Based on Convolution Channels , 2015, IEEE Transactions on Medical Imaging.
[2] Grace J Gang,et al. Task-based detectability in CT image reconstruction by filtered backprojection and penalized likelihood estimation. , 2014, Medical physics.
[3] Nooshin Kiarashi,et al. Task-based strategy for optimized contrast enhanced breast imaging: analysis of six imaging techniques for mammography and tomosynthesis. , 2014, Medical physics.
[4] Qihua Zhao,et al. Active pixel imagers incorporating pixel-level amplifiers based on polycrystalline-silicon thin-film transistors. , 2009, Medical physics.
[5] Jeffrey H Siewerdsen,et al. Comparison of model and human observer performance for detection and discrimination tasks using dual-energy x-ray images. , 2008, Medical physics.
[6] Arthur E Burgess,et al. Signal detection in power-law noise: effect of spectrum exponents. , 2007, Journal of the Optical Society of America. A, Optics, image science, and vision.
[7] Miguel P Eckstein,et al. Classification images for simple detection and discrimination tasks in correlated noise. , 2007, Journal of the Optical Society of America. A, Optics, image science, and vision.
[8] Miguel P Eckstein,et al. Evaluation of internal noise methods for Hotelling observer models. , 2007, Medical physics.
[9] Nancy A Obuchowski,et al. Incidence of advanced symptomatic disease as primary endpoint in screening and prevention trials. , 2007, AJR. American journal of roentgenology.
[10] Evaluation of Multiclass Model Observers in PET LROC Studies , 2007, IEEE Transactions on Nuclear Science.
[11] J H Siewerdsen,et al. Optimization of dual-energy imaging systems using generalized NEQ and imaging task. , 2006, Medical physics.
[12] Wei Zhao,et al. Amorphous selenium flat panel detectors for digital mammography: validation of a NPWE model observer with CDMAM observer performance experiments. , 2006, Medical physics.
[13] Ingrid Reiser,et al. Identification of simulated microcalcifications in white noise and mammographic backgrounds. , 2006, Medical physics.
[14] C. D'Orsi,et al. Diagnostic Performance of Digital Versus Film Mammography for Breast-Cancer Screening , 2005, The New England journal of medicine.
[15] Miguel P. Eckstein,et al. Automated optimization of JPEG 2000 encoder options based on model observer performance for detecting variable signals in X-ray coronary angiograms , 2004, IEEE Transactions on Medical Imaging.
[16] Luisa P. Wallace,et al. Changes in breast cancer detection and mammography recall rates after the introduction of a computer-aided detection system. , 2004, Journal of the National Cancer Institute.
[17] R. G. Wells,et al. A comparison of human and model observers in multislice LROC studies , 2005, 2003 IEEE Nuclear Science Symposium. Conference Record (IEEE Cat. No.03CH37515).
[18] Michael A. King,et al. Comparison of human- and model-observer LROC studies , 2003, SPIE Medical Imaging.
[19] H.H. Barrett,et al. Model observers for assessment of image quality , 1993, 2002 IEEE Nuclear Science Symposium Conference Record.
[20] H H Barrett,et al. Human- and model-observer performance in ramp-spectrum noise: effects of regularization and object variability. , 2001, Journal of the Optical Society of America. A, Optics, image science, and vision.
[21] P. Xue,et al. Dose efficiency and low-contrast detectability of an amorphous silicon x-ray detector for digital radiography. , 2000, Physics in medicine and biology.
[22] Craig K. Abbey,et al. Modeling Visual Detection Tasks in Correlated Image Noise with Linear Model Observers , 2000 .
[23] Peter G. J. Barten,et al. Contrast sensitivity of the human eye and its e ects on image quality , 1999 .
[24] A E Burgess,et al. The Rose model, revisited. , 1999, Journal of the Optical Society of America. A, Optics, image science, and vision.
[25] A E Burgess,et al. Visual signal detectability with two noise components: anomalous masking effects. , 1997, Journal of the Optical Society of America. A, Optics, image science, and vision.
[26] R. F. Wagner,et al. Objective assessment of image quality. II. Fisher information, Fourier crosstalk, and figures of merit for task performance. , 1995, Journal of the Optical Society of America. A, Optics, image science, and vision.
[27] A. Burgess. Comparison of receiver operating characteristic and forced choice observer performance measurement methods. , 1995, Medical physics.
[28] M P Eckstein,et al. Lesion detection in structured noise. , 1995, Academic radiology.
[29] A. Burgess. Statistically defined backgrounds: performance of a modified nonprewhitening observer model. , 1994, Journal of the Optical Society of America. A, Optics, image science, and vision.
[30] R. F. Wagner,et al. SNR and noise measurements for medical imaging: I. A practical approach based on statistical decision theory. , 1993, Physics in medicine and biology.
[31] Jie Yao,et al. Predicting human performance by a channelized Hotelling observer model , 1992, Optics & Photonics.
[32] H H Barrett,et al. Effect of random background inhomogeneity on observer detection performance. , 1992, Journal of the Optical Society of America. A, Optics and image science.
[33] H H Barrett,et al. Ideal versus human observer for long-tailed point spread functions: does deconvolution help? , 1991, Physics in medicine and biology.
[34] A B Watson,et al. Efficiency of a model human image code. , 1987, Journal of the Optical Society of America. A, Optics and image science.
[35] A J Ahumada,et al. Putting the visual system noise back in the picture. , 1987, Journal of the Optical Society of America. A, Optics and image science.
[36] H H Barrett,et al. Addition of a channel mechanism to the ideal-observer model. , 1987, Journal of the Optical Society of America. A, Optics and image science.
[37] Andrew B. Watson,et al. The cortex transform: rapid computation of simulated neural images , 1987 .
[38] R G Swensson,et al. Display thresholding of images and observer detection performance. , 1987, Journal of the Optical Society of America. A, Optics and image science.
[39] C. Metz. ROC Methodology in Radiologic Imaging , 1986, Investigative radiology.
[40] H. Barrett,et al. Effect of noise correlation on detectability of disk signals in medical imaging. , 1985, Journal of the Optical Society of America. A, Optics and image science.
[41] R. L. de Valois,et al. Relationship between spatial-frequency and orientation tuning of striate-cortex cells. , 1985, Journal of the Optical Society of America. A, Optics and image science.
[42] R. F. Wagner,et al. Unified SNR analysis of medical imaging systems , 1985, Physics in medicine and biology.
[43] D. Kersten. Spatial summation in visual noise , 1984, Vision Research.
[44] John A. Swets,et al. Evaluation of diagnostic systems : methods from signal detection theory , 1982 .
[45] R. F. Wagner,et al. Efficiency of human visual signal discrimination. , 1981, Science.
[46] Philip F. Judy,et al. Lesion detection and signal–to–noise ratio in CT images , 1981 .
[47] K. Hanson,et al. Detectability in computed tomographic images. , 1979, Medical physics.
[48] D. H. Kelly. Spatial frequency selectivity in the retina , 1975, Vision Research.
[49] Keinosuke Fukunaga,et al. Introduction to Statistical Pattern Recognition , 1972 .
[50] D. M. Green,et al. Signal detection theory and psychophysics , 1966 .
[51] A. Rose,et al. Quantum and noise limitations of the visual process. , 1953, Journal of the Optical Society of America.
[52] P. Mahalanobis. On the generalized distance in statistics , 1936 .