Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-27T01:38:56.909Z Has data issue: false hasContentIssue false

1 - Medical Image Perception

Published online by Cambridge University Press:  20 December 2018

By
Ehsan Samei  and
Elizabeth A. Krupinski
Edited by
Ehsan Samei  and
Elizabeth A. Krupinski
Ehsan Samei
Affiliation:
Duke University Medical Center, Durham
Elizabeth A. Krupinski
Affiliation:
Emory University, Atlanta
Get access

Summary

A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
The Handbook of Medical Image Perception and Techniques , pp. 1 - 8
Publisher: Cambridge University Press
Print publication year: 2018

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abbey, C.K., Bochud, F.O. (2000). Modeling visual detection tasks in correlated image noise with linear model observers. In: Beutel, J., Van Metter, R., Kundel, H. (eds.) Handbook of Medical Imaging. Vol. 1: Physics and Psychophysics. Bellingham, WA: SPIE Press, pp. 655–682.Google Scholar
Al Mohammad, B., Brennan, P.C., Mello-Thoms, C. (2017). A review of lung cancer screening and the role of computer-aided detection. Clin Radiol, 72, 433–442.Google Scholar
American Telemedicine Association Ocular Telehealth Special Interest Group. (2004). Telehealth practice recommendations for diabetic retinopathy. Telemed J eHealth, 10, 469–482.Google Scholar
America’s Health Insurance Plans (AHIP). (2008). Ensuring quality through appropriate use of diagnostic imaging. www.medsolutions.com/clinical_quality/facts/AHIP%202008%20Imaging%20Stats.pdf (last accessed June 15, 2017).Google Scholar
Badano, A., Revie, C., Casertano, A., Cheng, W.C., Green, P., Kimpe, T., Krupinski, E., Susson, C., Skrovseth, S., Treanor, D., Boynton, P., Clunie, D., Flynn, M.J., Heki, T., Hewitt, S., et al. (2015). Consistency and standardization of color in medical imaging: a consensus report. J Digit Imag, 28, 41–52.CrossRefGoogle ScholarPubMed
Balint, B.J., Steenburg, S.D., Lin, H., Shen, C., Steele, J.L., Gunderman, R.B. (2014). Do telephone call interruptions have an impact on radiology resident diagnostic accuracy? Acad Radiol, 21, 1623–1628.Google Scholar
Bashshur, R.L., Krupinski, E.A., Weinstein, R.S., Dunn, M.R., Bashshur, N. (2017). The empirical foundations of telepathology: evidence of feasibility and intermediate effects. Telemed eHealth, 23, 155–191.Google Scholar
Beam, C.A., Krupinski, E.A., Kundel, H.L., Sickles, E.A., Wagner, R.F. (2006). The place of medical image perception in 21st-dentury health care. J Am Coll Radiol, 3, 409–412.Google Scholar
Berbaum, K.S., Franken, E.A., Dorfman, D.D., et al. (1989). Satisfaction of search in diagnostic radiology. Invest Radiol, 25, 133–140.Google Scholar
Berbaum, K.S., Krupinski, E.A., Schartz, K.M., Caldwell, R.T., Madsen, M.T., Hur, S., Laroia, A.T., Thompson, B.H., Mullan, B.F., Franken, E.A. (2016). The influence of a vocalized checklist on detection of multiple abnormalities in chest radiography. Acad Radiol, 23, 413–420.Google Scholar
Berlin, L. (2005). Errors of omission. AJR, 185, 1416–1421.Google Scholar
Berlin, L. (2007). Accuracy of diagnostic procedures: has it improved over the past five decades? AJR, 188, 1173–1178.CrossRefGoogle ScholarPubMed
Bracamonte, E., Gibson, B.A., Klein, R., Krupinski, E.A., Weinstein, R.S. (2017). Communicating uncertainly in surgical pathology reports: a survey of staff physicians and residents at an academic medical center. Acad Pathol, 3, 1–7.Google Scholar
Brink, J.A., Arenson, R.L., Grist, T.M., Lewin, J.S., Enzmann, D. (2017). Bits and bytes: the future of radiology lies in informatics and information technology. Eur Radiol, 27, 3647–3651.Google Scholar
Carmody, D.P., Nodine, C.F., Kundel, H.L. (1980). An analysis of perceptual and cognitive factors in radiographic interpretation. Perception, 9, 339–344.CrossRefGoogle ScholarPubMed
Christensen, P.A., Lee, L.E., Thrall, M.J., Powell, S.Z., Chevez-Barrios, P., Long, S.W. (2017). RecutClub.com: an open source, whole slide image-based pathology education system. J Pathol Inform, 8, 10.Google Scholar
Dobbins, J.T., McAdams, P., Sabol, J.M., Chakraborty, D.P., Kazerooni, E.A., Reddy, G.P., Vikgren, J., Bath, M. (2017). Multi-institutional evaluation of digital tomosynthesis, dual-energy radiography, and conventional chest radiography for the detection and management of pulmonary nodules. Radiology, 282, 236–250.Google Scholar
Dodoo, M.S., Duszak, R., Hughes, D.R. (2013). Trends in utilization of medical imaging from 2003 to 2011: clinical encounters offer a complementary patient-centered focus. J Am Coll Radiol, 10, 507–512.Google Scholar
Doi, K. (2007). Computer-aided diagnosis in medical imaging: historical review, current status and future potential. Comput Med Imaging Graph, 31, 198–211.CrossRefGoogle ScholarPubMed
Fanshawe, T.R., Phillips, P., Plumb, A., Helbren, E., Halligan, S., Taylor, S.A., Gale, A., Mallett, S. (2016). Do prevalence expectations affect patterns of visual search and decision-making in interpreting CT colonography endoluminal videos? Br J Radiol, 89, 2010842.CrossRefGoogle ScholarPubMed
Fei, B., Schuster, D.M. (2017). PET molecular imaging-directed biopsy: a review. Am J Roentgenol, 209, 1–15.Google Scholar
Food and Drug Administration (FDA). (2017). www.fda.gov/newsevents/newsroom/pressannouncements/ucm552742.htm (accessed June 15, 2017).Google Scholar
Giger, M.S., Doi, K., MacMahon, H. (1988). Image feature analysis and computer-aided diagnosis in digital radiography. 3. Automated detection of nodules in peripheral lung fields. Med Phys, 15, 158–166.CrossRefGoogle ScholarPubMed
Gilbert, F.J., Tucker, L., Young, K.C. (2016). Digital breast tomosynthesis (DBT): a review of the evidence for use as a screening tool. Clin Radiol, 71, 141–150.CrossRefGoogle ScholarPubMed
Glabman, H. (2005). Health plans strain to contain rapidly rising costs of imaging. Managed Care magazine. www.managedcaremag.com/archives/0501/0501.imaging.html (accessed June 15, 2017).Google Scholar
Guolan, L., Fei, B. (2014). Medical hyperspectral imaging: a review. J Biomed Opt, 19, 10901.Google Scholar
Jha, S., Topol, E.J. (2016). Adapting to artificial intelligence: radiologists and pathologists as information specialists. JAMA, 316, 2353–2354.CrossRefGoogle ScholarPubMed
Kaplan, K.J., Rao, K.F. (2016). Digital Pathology: Historical Perspectives, Current Concepts and Future Applications, New York: Springer International Publishing.CrossRefGoogle Scholar
Kok, E. M., Jarodzka, H., de Bruin, A.B.H., BinAmir, H.A.N., Robben, S.G.F., van Merrienboer, J.J.G. (2016). Systematic viewing in radiology: seeing more, missing more? Adv Health Sci Educ Theory Pract, 21, 189–205.Google Scholar
Krupinski, E.A. (2016). Special section guest editorial: medical image perception: understanding how radiologists understand images. J Med Imag, 3, 011001.CrossRefGoogle ScholarPubMed
Krupinski, E.A., Jiang, Y. (2008). Evaluation of medical imaging systems. Med Phys, 35, 645–659.Google Scholar
Krupinski, E.A., Kallergi, M. (2007). Choosing a radiology workstation: technical and clinical considerations. Radiology, 242, 671–682.Google Scholar
Krupinski, E.A., Nypaver, M., Poropatich, R., et al. (2002). Clinical applications in telemedicine/telehealth. Telemed J e-Health, 8, 13–34.Google Scholar
Krupinski, E.A., Berbaum, K.S., Schartz, K.M., Caldwell, R.T., Madsen, M.T. (2017). The impact of fatigue on satisfaction of search in chest radiography. Acad Radiol, 24, 1058–1063.CrossRefGoogle ScholarPubMed
Kundel, H.L. (1975). Peripheral vision, structured noise and film reader error. Radiology, 114, 269–273.Google Scholar
Kundel, H.L., Nodine, C.F., Carmody, D. (1978). Visual scanning, pattern recognition and decision-making in pulmonary nodule detection. Invest Radiol, 13, 175–181.CrossRefGoogle ScholarPubMed
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
Lee, D.W., Duszak, R., Hughes, D.R. (2013). Comparative analysis of Medicare spending for medical imaging: sustained dramatic slowdown compared with other services. Am J Roentgenol, 201, 1277–1282.CrossRefGoogle ScholarPubMed
Levenson, R.M., Krupinski, E.A., Navarro, V.M., Wasserman, E.A. (2015). Pigeons (Columba livia) as trainable observers of pathology and radiology breast cancer images. PLoS One, 10, e0141357.CrossRefGoogle ScholarPubMed
Liang, G., Vo, D., Nguyen, P.K. (2017). Fundamentals of cardiovascular molecular imaging: a review of concepts and strategies. Curr Cardiovasc Imag Rep, 10, 8.Google Scholar
Littlefair, S., Mello-Thoms, C., Reed, W., Pietryzk, M., Lewis, S., McEntee, M., Brennan, P. (2016). Increasing prevalence expectation in thoracic radiology leads to overcall. Acad Radiol, 23, 284–289.Google Scholar
Manning, D.J., Gale, A., Krupinski, E.A. (2005). Perception research in medical imaging. Br J Radiol, 78, 683–685.Google Scholar
McKoy, K., Antoniotti, N.M., Armstrong, A., Bashshur, R., Bernard, J., Bernstein, D., Burdick, A., Edison, K., Goldyne, M., Kovarik, C., Krupinski, E.A., Kvedar, J., Larkey, J., Lee-Keltner, I., Lipoff, J.B., Oh, D.H., Pak, H., Seraly, M.P., Siegel, D., Tejasvi, T., Whited, J. (2016). Practice guidelines for teledermatology. Telemed eHealth, 22, 981–990.Google Scholar
Medicare Payment Advisory Commission (MEDPAC). (2014) Health Care Spending and the Medicare Program June 2016: a data book: healthcare spending and the Medicare Program. www.medpac.gov/docs/default-source/data-book/june-2016-data-book-health-care-spending-and-the-medicare-program.pdf?sfvrsn=0 (accessed June 15, 2017).Google Scholar
Metz, C.E. (2006). Receiver operating characteristic analysis: a tool for the quantitative evaluation of observer performance and imaging systems. J Am Coll Radiol, 3, 413–442.CrossRefGoogle ScholarPubMed
Nodine, C.F., Kundel, H.L. (1987). Using eye movements to study visual search and to improve tumor detection. RadioGraphics, 7, 1241–1250.Google Scholar
Nodine, C.F., Mello-Thoms, C. (2000). The nature of expertise in radiology. In Beutel, J., Van Metter, R., Kundel, H. (eds.) Handbook of Medical Imaging. Vol. 1: Physics and Psychophysics. Bellingham, WA: SPIE Press, pp. 859–894.CrossRefGoogle Scholar
Obuchowski, N.A. (2005). ROC analysis. Am J Roentgenol, 184, 364–372.Google Scholar
Pande, T., Cohen, C., Pai, M., Ahmed Khan, F. (2016). Computer-aided detection of pulmonary tuberculosis on digital chest radiographs: a systematic review. Int J Tuberc Lung Dis, 20, 1226–1230.Google Scholar
Pantanowitz, L., Dickinson, K., Evans, A.J., Hassell, L.A., Henricks, W.H., Lennerz, J.K., Lowe, A., Parwani, A.V., Riben, M., Smith, D., Tuthill, J.M., Weinstein, R.S., Wilbur, D.C., Krupinski, E.A., Bernard, J. (2014). American Telemedicine Association clinical guidelines for telepathology. Telemed e-Health, 20, 1049–1056.Google Scholar
Ratwani, R.M., wang, E., Fong, A., Cooper, C.J. (2016). A human factors approach to understanding the types and sources of interruptions in radiology reading rooms. J Am Coll Radiol, 13, 1102–1105.Google Scholar
Rohatgi, S., Hanna, T.N., Sliker, C.W., Abbott, R.M., Nicola, R. (2015). After-hours radiology: challenges and strategies for the radiologist. Am J Roentgenol, 205, 956–961.Google Scholar
Samei, E., Flynn, M.J., Kearfott, K.J. (1997). Patient dose and detectability of subtle lung nodules in digital chest radiographs. Health Physics, 72(6S).Google Scholar
Sim, D.A., Mitry, D., Alexander, P., Mapani, A., Goverdhan, S., Aslam, T., Tufail, A., Egan, C.A., Keane, P.A. (2016). The evolution of teleophthalmology programs in the United Kingdom: beyond diabetic retinopathy. J Diabetes Sci Technol, 10, 308–317.CrossRefGoogle ScholarPubMed
Smith, M.J. (1967). Error and Variation in Diagnostic Radiology. Springfield, IL: Charles C. Thomas.Google Scholar
Tan, I.J., Dobson, L.P., Bartnik, S., Muir, J., Turner, A.W. (2017). Real-time teleophthalmology versus face-to-face consultation: a systematic review. J Telemed Telecare, 23, 629–638.Google Scholar
Theurer, L., Bashshur, R., Bernard, J., Brewer, T., Busch, J., Caruso, D., Coccaro-Word, B., Kemalyan, N., Leenknecht, C., McMillan, L.R., Pham, T., Saffle, J.R., Krupinski, E.A. (2017). American Telemedicine guidelines for teleburn. Telemed eHealth, 23, 365–375.CrossRefGoogle ScholarPubMed
Tuddenham, W.J. (1962). Visual search, image organization, and reader error in roentgen diagnosis: studies of psychophysiology of roentgen image perception. Radiology, 78, 694–704.Google Scholar
Tuddenham, W.J. (1963). Problems of perception in chest roentgenology: facts and fallacies. Radiol Clin North Am, 1, 227–289.Google Scholar
Van der Gijp, A., Ravensloot, C.J., Jarodzka, H., van der Schaaf, M.F., van der Schaaf, I.C., van Schaik, J.P.J., ten Cate, T.J. (2017). How visual search relates to visual diagnostic performance: a narrative systematic review of eye-tracking research in radiology. Adv Health Sci Educ Theory Pract, 22, 765–767.CrossRefGoogle ScholarPubMed
Wagner, R.F., Metz, C.E., Campbell, G. (2007). Assessment of medical imaging systems and computer aids: a tutorial review. Acad Radiol, 14, 723–748.Google Scholar
Waite, S., Scott, J., Gale, B., Fuchs, T., Kolla, S., Reede, D. (2017a). Interpretative error in radiology. Am J Roentgenol, 208, 739–749.Google Scholar
Waite, S., Kolla, S., Jeudy, J., Legasto, A., Macknik, S.L., Martinez-Conde, S., Krupinski, E.A., Reede, D.L. (2017b). Tired in the reading room: the influence of fatigue in radiology. J Am Coll Radiol, 14, 191–197.Google Scholar
Ware, J.B., Jha, S., Hoang, J.K., Baker, S., Wruble, J. (2017). Effective radiology reporting. J Am Coll Radiol, 14, 838–839.Google Scholar
Weinstein, R.S., Descour, M.R., Liang, C., Bhattacharyya, A.K., et al. (2001). Telepathology overview: from concept to implementation. Human Pathol, 32, 1283–1299.Google Scholar
Wilbur, D.C. (2016). Digital pathology and its role in cytology education. Cytopathology, 27, 325–330.Google Scholar
Williams, L.H., Drew, T. (2017). Distraction in diagnostic radiology: how is search through volumetric medical images affected by interruptions? Cogn Res Princ Implic, 2, 12Google Scholar
Wolfe, J.M. (2016). Use-inspired basic research in medical image perception. Cogn Res, 1, 17.Google Scholar
Wolfe, J.M., Evans, K.K., Drew, T., Aizenman, A., Josephs, E. (2016). How do radiologists use the human search engine? Radiat Prot Dosimetry, 169, 24–31.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×