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2 - A Short History of Image Perception in Medical Radiology

from Part I - Historical Reflections and Theoretical Foundations

Published online by Cambridge University Press:  20 December 2018

By
Harold Kundel  and
Calvin F. Nodine
Edited by
Ehsan Samei  and
Elizabeth A. Krupinski
Ehsan Samei
Affiliation:
Duke University Medical Center, Durham
Elizabeth A. Krupinski
Affiliation:
Emory University, Atlanta
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The Handbook of Medical Image Perception and Techniques , pp. 11 - 22
Publisher: Cambridge University Press
Print publication year: 2018

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References

Appiah, K.A. (2008). Experiments in Ethics. Cambridge, MA: Harvard University Press.Google Scholar
Barrett, H.H., Myers, K.J. (2003). Foundations of Image Science. Hoboken, NJ: John Wiley.Google Scholar
Béclère, A. (1964). A physiologic study of vision in fluoroscopic examinations. In: Bruwer, A. (ed.) Classic Descriptions in Diagnostic Roentgenology. Springfield, IL: Charles C. Thomas.Google Scholar
Beiden, S.V., Wagner, R.F., Campbell, G., et al. (2001). Components-of-variance models for random-effects ROC analysis: the case of unequal variance structures across modalities. Acad Radiol, 8, 605–615.Google Scholar
Berbaum, K.S., Dorfman, D.D., Franken, E.A., Jr. (1989). Measuring observer performance by ROC analysis: indications and complications. Invest Radiol, 24, 228–233.Google Scholar
Berbaum, K.S., Franken, E.A., Jr., Dorfman, D.D., et al. (1990). Satisfaction of search in diagnostic radiology. Invest Radiol, 25, 133–140.Google Scholar
Berbaum, K.S., Franken, E.A., Jr., Dorfman, D.D., et al. (1991). Time course of satisfaction of search. Invest Radiol, 26, 640–648.Google Scholar
Berbaum, K.S., El-Khoury, G.Y., Franken, E.A., Jr. (1994). Missed fractures resulting from satisfaction of search effect. Emerg Radiol, 1, 242–249.Google Scholar
Berbaum, K.S., Franken, E.A., Jr., Dorfman, D.D., et al. (2000). Role of faulty decision making in the satisfaction of search effect in chest radiography. Acad Radiol, 7, 1098–1106.Google Scholar
Berbaum, K.S., Brandser, E.A., Franken, E.A., et al. (2001). Gaze dwell times on acute trauma injuries missed because of satisfaction of search. Acad Radiol, 8, 304–314.CrossRefGoogle ScholarPubMed
Birkelo, C.C., Chamberlain, W.E., Phelps, P.S., et al. (1947). Tuberculosis case finding. A comparison of the effectiveness of various roentgenographic and photofluorographic methods. JAMA, 133, 359–366.Google Scholar
Bunch, P.C., Hamilton, J.F., Sanderson, G.K., et al. (1978). A free-response approach to the measurement and characterization of radiographic observer performance. J Appl Photogr Eng, 4, 166–171.Google Scholar
Burger, G.C.E. (1949). The perceptibility of details in roentgen examinations of the lung. Acta Radiol Diag, 31, 193–222.Google Scholar
Burger, G.C.E. (1950). Phantom tests with X-ray. Philips Technical Review, 11, 291–298.Google Scholar
Burger, G.C.E., Van Dijk, B. (1936). Über die physiologischen Grundlagen der Durchleuchtung. Fortschr Rontg, 54, 492–496.Google Scholar
Burgess, A.E. (1995). Image quality, the ideal observer, and human performance of radiologic detection tasks. Acad Radiol, 2, 522–526.Google Scholar
Burgess, A.E. (1999). The Rose model, revisited. J Opt Soc Am A, 16, 633–646.CrossRefGoogle ScholarPubMed
Burgess, A.E., Wagner, R.F., Jennings, R.J., et al. (1981). Efficiency of human visual signal discrimination. Science, 214, 93–94.Google Scholar
Chakraborty, D.P. (1989). Maximum likelihood analysis of free response operating characteristic (FROC) data. Med Phys, 16, 561–568.Google Scholar
Chakraborty, D.P. (2002). Statistical power in observer performance studies: comparison of receiver operating characteristic and free-response methods in tasks involving localization. Acad Radiol, 9, 147–156.Google Scholar
Chakraborty, D.P., Berbaum, K.S. (2004). Observer studies involving detection and localization: modeling, analysis, and validation. Med Phys, 31, 2313–2330.CrossRefGoogle ScholarPubMed
Chamberlain, W.E. (1942). Fluoroscopes and fluoroscopy. Radiology, 38, 383–412.CrossRefGoogle Scholar
Chesters, M.S. (1992). Human visual perception and ROC methodology in medical imaging. Phys Med Biol, 37, 1433–1476.Google Scholar
Coltman, J.W. (1948). Fluoroscopic image brightening by electronic means. Radiology, 51, 359–367.Google Scholar
De Vries, H. (1943). The quantum character of light and its bearing upon threshold of vision, the differential sensitivity and visual acuity of the eye. Physica, 10, 553–564.Google Scholar
Dodd, L.E., Wagner, R.F., Armato, S.G., 3rd, et al. (2004). Assessment methodologies and statistical issues for computer-aided diagnosis of lung nodules in computed tomography: contemporary research topics relevant to the lung image database consortium. Acad Radiol, 11, 462–475.Google Scholar
Doi, K. (2006). Diagnostic imaging over the last 50 years: research and development in medical imaging science and technology. Phys Med Biol, 51, R5–27.Google Scholar
Dorfman, D., Alf, E.J. (1969). Maximum likelihood estimation of parameters of signal-detection theory and determination of confidence intervals – rating method data. J Math Psych, 6, 487–496.Google Scholar
Dorfman, D.D., Berbaum, K.S., Metz, C.E. (1992). Receiver operating characteristic analysis. Generalization to the population of readers and patients with the jackknife method. Invest Radiol, 27, 723–731.Google Scholar
Eckstein, M.P. (2001). The perception of medical images 1941–2001. Opt Photonics News, 12, 34–40.Google Scholar
Eckstein, M., Whiting, J. (1995). Lesion detection in structured noise. Acad Radiol, 2, 249–253.Google Scholar
Editorial (1947). The “personal equation” in the interpretation of a chest roentgenogram. JAMA, 133, 399–400.Google Scholar
Editorial (1994). The accuracy of mammographic interpretation. N Engl J Med, 331, 1521–1522.Google Scholar
Edwards, D.C., Kupinski, M.A., Metz, C.E., et al. (2002). Maximum likelihood fitting of FROC curves under an initial-detection-and-candidate-analysis model. Med Phys, 29, 2861–2870.Google Scholar
Egan, J., Greenberg, G., Schulman, A. (1961). Operating characteristics, signal detectability, and the method of free response. J Acoust Soc Am, 33, 993–1007.Google Scholar
Elliott, P. (1964) Tables of d ’. In: Swets, J. (ed.) Signal Detection and Recognition by Human Observers. New York: John Wiley.Google Scholar
Elmore, J.G., Wells, C.K., Lee, C.H., et al. (1994). Variability in radiologists’ interpretation of mammograms. N Engl J Med, 331, 1493–1499.Google Scholar
Engel, F.L. (1971). Visual conspicuity, directed attention and retinal locus. Vision Res, 11, 563–567.Google Scholar
Felson, B., Morgan, W.K., Bristol, L.J., et al. (1973). Observations on the results of multiple readings of chest films in coal miners’ pneumoconiosis. Radiology, 109, 19–23.Google Scholar
Garland, L.H. (1949). On the scientific evaluation of diagnostic procedures. Radiology, 52, 309–328.Google Scholar
Garland, L.H. (1959). Studies on the accuracy of diagnostic procedures. AJR Am J Roentgenol, 82, 25–38.Google Scholar
Gitlin, J.N., Cook, L.L., Linton, O.W., et al. (2004). Comparison of “B” readers’ interpretations of chest radiographs for asbestos related changes. Acad Radiol, 11, 843–856.Google Scholar
Goddard, P., Leslie, A., Jones, A., et al. (2001). Error in radiology. Br J Radiol, 74, 949–951.Google Scholar
Goodenough, D.J., Rossmann, K., Lusted, L.B. (1972). Radiographic applications of signal detection theory. Radiology, 105, 199–200.Google Scholar
Goodenough, D.J., Rossmann, K., Lusted, L.B. (1974). Radiographic applications of receiver operating characteristic (ROC) curves. Radiology, 110, 89–95.Google Scholar
Green, D.M., Swets, J.A. (1966). Signal Detection Theory and Psychophysics. New York: John Wiley.Google Scholar
Green, D.M., Swets, J.A. (1974). Signal Detection Theory and Psychophysics. Huntington, NY: Krieger.Google Scholar
Gur, D., King, J.L., Rockette, H.E., et al. (1989). Practical issues of experimental ROC analysis. Invest Radiol, 25, 583–586.Google Scholar
Hanley, J.A. (1989). Receiver operating characteristic (ROC) methodology: the state of the art. Crit Rev Diagn Im, 29, 307–355.Google Scholar
Hanley, J.A., McNeil, B.J. (1983). A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology, 148, 839–843.Google Scholar
Henkelman, R.M., Kay, I., Bronskill, M.J. (1990). Receiver operating characteristic (ROC) analysis without truth. Med Decis Making, 10, 24–29.Google Scholar
Hillis, S.L., Berbaum, K.S. (2004). Power estimation for the Dorfman–Berbaum-Metz method. Acad Radiol, 11, 1260–1273.Google Scholar
Hillis, S.L., Obuchowski, N.A., Schartz, K.M., et al. (2005). A comparison of the Dorfman-Berbaum-Metz and Obuchowski-Rockette methods for receiver operating characteristic (ROC) data. Stat Med, 24, 1579–1607.CrossRefGoogle ScholarPubMed
Horvath, W., Tolles, W., Bostrom, R. (1956). Quantitative measurements of cell properties on Papanicolaou smears as criteria for screening. In: First International Cancer Cytology Congress. Chicago, IL: American Cancer Society.Google Scholar
Hu, C.H., Kundel, H.L., Nodine, C.F., et al. (1994). Searching for bone fractures: a comparison with pulmonary nodule search. Acad Radiol, 1, 25–32.Google Scholar
Krupinski, E.A. (1996). Visual scanning patterns of radiologists searching mammograms. Acad Radiol, 3, 137–144.Google Scholar
Krupinski, E.A., Lund, P.J. (1997). Differences in time to interpretation for evaluation of bone radiographs with monitor and film viewing. Acad Radiol, 4, 177–182.Google Scholar
Krupinski, E.A., Nodine, C.F., Kundel, H.L. (1998). Enhancing recognition of lesions in radiographic images using perceptual feedback. Opt Eng, 37, 813–818.Google Scholar
Kuhl, D.E., Sanders, T.D., Edwards, R.Q., et al. (1972). Failure to improve observer performance with scan smoothing. J Nucl Med, 13, 752–757.Google Scholar
Kundel, H.L. (1979). Images, image quality and observer performance. Radiology, 132, 265–271.Google Scholar
Kundel, H. (2006). History of research in medical image perception. J Am Col Radiol, 3, 402–408.Google Scholar
Kundel, H.L., LaFollette, P.S. (1972). Visual search patterns and experience with radiological images. Radiology, 103, 523–528.Google Scholar
Kundel, H.L., Nodine, C.F. (1975). Interpreting chest radiographs without visual search. Radiology, 116, 527–532.Google Scholar
Kundel, H.L., Polansky, M. (1997). Mixture distribution and receiver operating characteristic analysis of bedside chest imaging using screen-film and computed radiography. Acad Radiol, 4, 1–7.Google Scholar
Kundel, H.L., Revesz, G. (1976). Lesion conspicuity, structured noise, and film reader error. AJR Am J Roentgenol, 126, 1233–1238.Google Scholar
Kundel, H.L., Wright, D.J. (1969). The influence of prior knowledge on visual search strategies during the viewing of chest radiographs. Radiology, 93, 315–320.CrossRefGoogle ScholarPubMed
Kundel, H.L., Revesz, G., Stauffer, H.M. (1968). Evaluation of a television image processing system. Invest Radiol, 3, 44–50.Google Scholar
Kundel, H.L., Revesz, G., Stauffer, H.M. (1969). The electro-optical processing of radiographic images. Radiol Clin N Am, 7, 447–460.Google Scholar
Kundel, H.L., Nodine, C.F., Carmody, D.P. (1978). Visual scanning, pattern recognition, and decision making in pulmonary nodule detection. Invest Radiol, 13, 175–181.Google Scholar
Kundel, H.L., Nodine, C.F., Krupinski, E.A. (1989). Searching for lung nodules: visual dwell indicates locations of false-positive and false-negative decisions. Invest Radiol, 24, 472–478.Google Scholar
Kundel, H.L., Nodine, C.F., Krupinski, E.A. (1990). Computer displayed eye position as a visual aid to pulmonary nodule interpretation. Invest Radiol, 25, 890–896.Google Scholar
Kundel, H.L., Polansky, M., Phelan, M. (2001). Evaluating imaging systems in the absence of truth: a comparison of ROC analysis and mixture distribution analysis using CAD in mammography. Proc Soc Photo-Opt Instrum Eng, 4324, 153–158.Google Scholar
Kundel, H.L., Nodine, C.F., Conant, E.F., et al. (2007). Holistic component of image perception in mammogram interpretation: gaze-tracking study. Radiology, 242, 396–402.Google Scholar
Kupinski, M.A., Watson, A.B., Siewerdsen, J.H., et al. (2007). Image quality. J Opt Soc Am A, 24, B198.Google Scholar
Lesgold, A., Rubinson, H., Feltovich, P., et al. (1988). Expertise in a complex skill: Diagnosing X-ray pictures. In: Chi, M., Glaser, R., Farr, M. (eds.) The Nature of Expertise. Hillsdale, NJ: Erlbaum.Google Scholar
Lusted, L.B. (1960). Logical analysis in roentgen diagnosis. Radiology, 74, 178–193.Google Scholar
Lusted, L.B. (1968). Introduction to Medical Decision Making. Springfield, IL: Charles C. Thomas.Google Scholar
Lusted, L.B. (1969). Perception of the roentgen image: applications of signal detection theory. Radiol Clin N Am, 7, 435–445.Google Scholar
Lusted, L.B. (1978). General problems in medical decision making with comments on ROC analysis. Semin Nucl Med, 8, 299–306.Google Scholar
Lusted, L.B. (1984). Editorial: ROC recollection. Med Decis Making, 4, 131–134.Google Scholar
Manning, D.J., Gale, A., Krupinski, E.A. (2005). Perception research in medical imaging. Br J Radiol, 78, 683–685.Google Scholar
McNeil, B.J., Keeler, E., Adelstein, S.J. (1975). Primer on certain elements of medical decision making. N Engl J Med, 292, 211–215.Google Scholar
Mello-Thoms, C., Dunn, S.M., Nodine, C.F., et al. (2003). The perception of breast cancers – a spatial frequency analysis of what differentiates masses from reported cancers. IEEE T Med Imaging, 22, 1297–1306.Google Scholar
Metz, C.E. (1978). Basic principles of ROC analysis. Semin Nucl Med, 8, 283–298.Google Scholar
Metz, C.E. (1989). Some practical issues of experimental design and data analysis in radiographic ROC studies. Invest Radiol, 24, 235–245.Google Scholar
Metz, C.E. (2007). ROC analysis in medical imaging: a tutorial review of the literature. Radiol Phys Tech, 1, 2–12.Google Scholar
Metz, C.E., Goodenough, D.J. (1973). Letter: On failure to improve observer performance with scan smoothing: a rebuttal. J Nucl Med, 14, 873–876.Google Scholar
Metz, C.E., Goodenough, D.J., Rossmann, K. (1973). Evaluation of receiver operating characteristic curve data in terms of information theory, with applications in radiography. Radiology, 109, 297–303.Google Scholar
Morgan, R.H. (1966). Visual perception in fluoroscopy and radiography. Annual oration in memory of John D. Reeves, Jr., M.D., 1924–1964. Radiology, 86, 403–416.Google Scholar
Myers, K.J. (2000). Ideal observer models of visual signal detection. In: Beutel, J., Kundel, H.L., Van Metter, R.L. (eds.) Handbook of Medical Imaging. Bellingham, WA: SPIE Press.Google Scholar
Newell, R.R., Chamberlain, W.E., Rigler, L. (1954). Descriptive classification of pulmonary shadows: a revelation of unreliability in the roentgen diagnosis of tuberculosis. Am Rev Tuberc, 69, 566–584.Google Scholar
Nodine, C.F., Kundel, H.L., Lauver, S.C., et al. (1996). The nature of expertise in searching mammograms for masses. Proc Soc Photo-Opt Instrum Eng, 2712, 89–94.Google Scholar
Norman, G.R., Coblentz, C.L., Brooks, L.R., et al. (1992). Expertise in visual diagnosis: a review of the literature. Acad Med, 67, S78–S83.Google Scholar
Obuchowski, N.A. (2000). Sample size tables for receiver operating characteristic studies. AJR Am J Roentgenol, 175, 603–608.Google Scholar
Obuchowski, N. (2005). Fundamentals of clinical research for radiologists, ROC analysis. AJR Am J Roentgenol, 184, 364–372.Google Scholar
Obuchowski, N.A., Lieber, M.L., Powell, K.A. (2000). Data analysis for detection and localization of multiple abnormalities with application to mammography. Acad Radiol, 7, 516–525.Google Scholar
Oestmann, J.W., Greene, R., Kushner, D.C., et al. (1988). Lung lesions: correlation between viewing time and detection. Radiology, 166, 451–453.Google Scholar
Perconti, P., Loew, M.H. (2007). Salience measure for assessing scale-based features in mammograms. J Opt Soc Am A, 24, B81–B90.Google Scholar
Proctor, R.W., Dutta, A. (1995). Perceptual skill/the development of expertise. In: Skill Acquisition and Human Performance. Thousand Oaks, CA: Sage Publications.Google Scholar
Renfrew, D.L., Franken, E.A., Jr., Berbaum, K.S., et al. (1992). Error in radiology: classification and lessons in 182 cases presented at a problem case conference. Radiology, 183, 145–150.Google Scholar
Revesz, G. (1985). Conspicuity and uncertainty in the radiographic detection of lesions. Radiology, 154, 625–628.Google Scholar
Revesz, G., Kundel, H.L., Graber, M.A. (1974). The influence of structured noise on the detection of radiologic abnormalities. Invest Radiol, 9, 479–486.Google Scholar
Revesz, G., Kundel, H.L., Bonitatibus, M. (1983). The effect of verification on the assessment of imaging techniques. Invest Radiol, 18, 194–198.Google Scholar
Robinson, P.J.A. (1997). Radiology’s Achilles’ heel: error and variation in the interpretation of the roentgen image. Br J Radiol, 70, 1085–1098.Google Scholar
Rose, A. (1948). The sensitivity performance of the human eye on an absolute scale. J Opt Soc Am, 38, 196–208.Google Scholar
Rossmann, K. (1969). Image quality. Radiol Clin N Am, 7, 419–433.Google Scholar
Rossmann, K., Wiley, B.E. (1970). The central problem in the study of radiographic image quality. Radiology, 96, 113–118.Google Scholar
Samei, E., Flynn, M.J., Eyler, W. (1999). Detection of subtle lung nodules: relative influence of quantum and anatomic noise on chest radiographs. Radiology, 213, 727–734.Google Scholar
Samei, E., Flynn, M.J., Peterson, E., et al. (2003). Subtle lung nodules: influence of local anatomic variations on detection. Radiology, 228, 76–84.Google Scholar
Samuel, S., Kundel, H.L., Nodine, C.F., et al. (1995). Mechanism of satisfaction of search: eye position recordings in the reading of chest radiographs. Radiology, 194, 895–902.Google Scholar
Schade, O.S. (1964). Modern image evaluation and television (the influence of electronic television on the methods of image evaluation). Appl Optics, 3, 17–21.Google Scholar
Smith, M.J. (1967) Error and Variation in Diagnostic Radiology. Springfield, IL: Thomas.Google Scholar
Starr, S.J., Metz, C.E., Lusted, L.B., et al. (1975). Visual detection and localization of radiographic images. Radiology, 116, 533–538.Google Scholar
Stigler, S.M. (1968). The History of Statistics. Cambridge, MA: Harvard University Press, pp. 240–242.Google Scholar
Swensson, R.G. (1993). Measuring detection and localization performance. In: Barrett, H.H., Gmitro, A.F. (eds.) Information Processing in Medical Imaging. New York, NY: Springer-Verlag.Google Scholar
Swensson, R. (1996). Unified measurement of observer performance in detecting and localizing target objects on images. Med Phys, 23, 1709–1725.Google Scholar
Swensson, R. (2000). Using localization data from image interpretations to improve estimates of performance accuracy. Med Decis Making, 20, 170–185.Google Scholar
Swets, J.A., Pickett, R.M. (1982). Evaluation of Diagnostic Systems. Methods from Signal Detection Theory. New York, NY: Academic Press.Google Scholar
Swets, J.A., Pickett, R.M., Whitehead, S.F., et al. (1979). Assessment of diagnostic technologies. Science, 205, 753–759.Google Scholar
Thomas, E.L., Lansdown, E.L. (1963). Visual search patterns of radiologists in training. Radiology, 81, 288–291.Google Scholar
Tuddenham, W.J. (1962). Visual search, image organization, and reader error in roentgen diagnosis. Radiology, 78, 694–704.Google Scholar
Tuddenham, W.J., Calvert, W.P. (1961). Visual search patterns in roentgen diagnosis. Radiology, 76, 255–256.Google Scholar
Wagner, R.F., Brown, D.G. (1985). Unified SNR analysis of medical imaging systems. Phys Med Biol, 30, 489–518.Google Scholar
Wood, B.P. (1999). Visual expertise. Radiology, 211, 1–3.Google Scholar
Yerushalmy, J. (1969). The statistical assessment of the variability in observer perception and description of roentgenographic pulmonary shadows. Radiol Clin N Am, 7, 381–392.Google Scholar
Yerushalmy, J., Harkness, J.T., Cope, J.H., et al. (1950). The role of dual reading in mass radiography. Am Rev Tuberc, 61, 443–464.Google Scholar
Zhou, X.-H., Obuchowski, N.A., McClish, D.K. (2002). Statistical Methods in Diagnostic Medicine. New York: John Wiley.Google Scholar

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