Abstract
Radiologic diagnosis relies on human beings seeing, perceiving, and processing images. Some of these steps are well understood, while others are being actively studied. A thorough understanding of how display monitors work and how human perception works is critical to optimizing the interactions between humans and computers. Mammography is a specialized topic within radiology, with unique IT requirements.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bevins NB, Silosky MS, Badano A, Marsh RM, Flynn MJ, Walz-Flannigan AI. Practical application of AAPM Report 270 in display quality assurance: a report of Task Group 270. Med Phys. 2020; https://doi.org/10.1002/mp.14227.
McKoy K, Antoniotti NM, Armstrong A, Basjshur R, Bernard J, Bernstein D, Burdick A, Edison K, Goldyne M, Kovarik C, Krupinski EA, Kvedar J, Larkey J, Lee-Keltner I, Lipoff JB, Oh DH, Pak H, Seraly MP, Siegel D, Tejasvi T, Whited J. Practice guidelines for teledermatology. Telemed J E Health. 2016;12:981–90.
Pantanowitz L, Dickinson K, Evans AJ, Hassell LA, Henricks WH, Lennerz JK, Lowe A, Parwani AV, Riben M, Smith D, Tuthill JM, Weinstein RS, Wilbur DC, Krupinski EA, Bernard J. American Telemedicine Association clinical guidelines for telepathology. J Pathol Inform. 2014;5:39.
Snowden R, Thompson P, Troscianko T. Basic vision: an introduction to visual perception. Oxford: Oxford University Press; 2012.
Ruckdeschel TG, Keener CR, Kofler JM, Nagy P, Samei E, Andriole KP, Krupinski E, Seibert JA, Towbin AJ, Bevins NB, Lewis DA. ACR-AAPM-SIIM technical standard for electronic practice of medical imaging. 2017. https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwi1kpfS0qzrAhWHnOAKHZ-lAOIQFjAAegQIBxAB&url=https%3A%2F%2Fwww.acr.org%2F-%2Fmedia%2FACR%2FFiles%2FPractice-Parameters%2Felec-practice-medimag.pdf&usg=AOvVaw2lDxY5useu0iV_lclhBK9Z.
Badano A, Revie C, Casertano A, Cheng WC, Green P, Kimpe T, Krupinski E, Sisson C, Skrovseth S, Treanor D, Boynton P, Clunie D, Flynn MJ, Heki T, Hewitt S, Homma H, Masia A, Matsui T, Nagy B, Nishibori M, Penczek J, Schopf T, Yagi Y, Yokoi H, Summit on Color in Medical Imaging. Consistency and standardization of color in medical imaging: a consensus report. J Digit Imaging. 2015;28:41–52.
Abel JT, Ouillette P, Williams CL, Blau J, Cheng J, Yao K, Lee WY, Cornish TC, Balis UGJ, McClintock DS. Display characteristics and their impact on digital pathology: a current review of pathologists’ future “microscope”. J Pathol Inform. 2020;11:23.
Elsayed M, Kadom N, Ghobadi C, Strauss B, Al Dandan O, Aggarwal A, Anzai Y, Griffith B, Lazarow F, Straus CM, Safdar NM. Virtual and augmented reality: potential applications in radiology. Acta Radiol. 2020;61(9):1258–65. https://doi.org/10.1177/0284185119897362.
Uppot RN, Laguna B, McCarthy CJ, De Novi G, Phelps A, Siegel E, Courtier J. Implementing virtual and augmented reality tools for radiology education and training, communication and clinical care. Radiology. 2019;291:570–80.
American Association of Physicists in Medicine. Task Group 18: assessment of display performance for medical imaging systems. https://www.aapm.org/pubs/reports/detail.asp. Last accessed 25 Aug 2020.
Monitor Calibration Methods. http://www.drycreekphoto.com/Learn/monitor_calibration.htm. Last accessed 7 May 2008.
American College of Radiology Practice Guideline for Digital Radiography. https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwjQi9jUnbfrAhXodN8KHY2gCdQQFjAAegQIARAB&url=https%3A%2F%2Fwww.acr.org%2F-%2Fmedia%2FACR%2FFiles%2FPractice-Parameters%2FRad-Digital.pdf&usg=AOvVaw0_I3Pp50hchLkpWHicxLMr. Last accessed 25 Aug 2020.
Dikici E, Bigelow M, Prevedello LM, White RD, Erdal BS. Integrating AI into radiology workflow: levels of research, production, and feedback maturity. J Med Imaging. 2020;7:016502.
Kotter E, Ranschaert E. Challenges and solutions for introducing artificial intelligence (AI) into daily clinical workflow. Eur Radiol. 2021;31:5–7. https://doi.org/10.1007/s00330-020-07148-2.
Jacobson FL. Medical image perception research in the emerging age of artificial intelligence. Radiology. 2020;294:210–1.
Seidel RL, Krupinski EA. Optimizing ergonomics in breast imaging. J Breast Imaging. 2019;1:234–8.
Degnan AJ, Ghobadi EH, Hardy P, Krupinski E, Scali EP, Stratchko L, Ulano A, Walker E, Wasnik AP, Auffermann WF. Perceptual and interpretative error in diagnostic radiology – causes and potential solutions. Acad Radiol. 2019;26:833–45.
Texeira PAG, Leplat C, Lombard C, Rauch A, Germain E, Waled AA, Jendoubi S, Bonarelli C, Padoin P, Simon L, Gillet R, Blum A, Nancy Radiology Ergonomics Group. Alternative PACS interface devices are well-accepted and may reduce radiologist’s musculoskeletal discomfort as compared to keyboard-mouse-recording device. Eur Radiol. 2020;30:5200–8.
Grigorian A, Fang P, Kirk T, Efendizade A, Jadidi J, Sighary M, Cohen-Addad DI. Learning from gamers: integrating alternative input devices and AutoHotkey scripts to simplify repetitive tasks and improve workflow. Radiographics. 2020;40:141–50.
Taylor-Phillips S, Stinton C. Fatigue in radiology: a fertile area for future research. Br J Radiol. 2019;92:20190043.
Zhan H, Schartz K, Zygmont ME, Johnson JO, Krupinski EA. The impact of fatigue on complex CT case interpretation by radiology references. Acad Radiol. 2021;28(3):424–32. https://doi.org/10.1016/j.acra.2020.06.005.
Stec N, Arje D, Moody AR, Krupinski EA, Tyrell PN. A systematic review of fatigue in radiology: is it a problem? Am J Roentgenol. 2018;210:799–806.
Hanna TN, Zygmont ME, Peterson R, Theriot D, Shekhani H, Johnson JO, Krupinski EA. The effects of fatigue from overnight shifts on radiology search patterns and diagnostic performance. J Am Coll Radiol. 2018;15:1709–16.
Waite S, Kolla S, Jeudy J, Legasto A, Macknik SL, Martinez-Conde S, Krupinski EA, Reede DL. Tired in the reading room: the influence of fatigue in radiology. J Am Coll Radiol. 2017;14:191–7.
Nihashi T, Ishigaki T, Satake H, Ito S, Kaii O, Mori Y, Shimamoto K, Fukushima H, Suzuki K, Umakoshi H, Ohashi M, Kawaguchi F, Naganawa S. Monitoring of fatigue in radiologists during prolonged image interpretation using fNIRS. Jpn J Radiol. 2019;37:437–48.
Krupinski EA, Berbaum KS, Caldwell RT, Schartz KM, Kim J. Long radiology workdays reduce detection and accommodation accuracy. J Am Coll Radiol. 2010;7:698–704.
Krupinski EA, Berbaum KS. Measurement of visual strain in radiologists. Acad Radiol. 2009;16:947–50.
Krupinski EA, Berbaum KS, Schartz KM, Caldwell RT, Madsen MT. The impact of fatigue on satisfaction of search in chest radiography. Acad Radiol. 2017;24:1058–63.
Krupinski EA, Berbaum KS, Caldwell RT, Schartz KM, Madsen MT, Kramer DJ. Do long radiology workdays affect nodule detection in dunamic CT interpretation? J Am Coll Radiol. 2012;9:191–8.
Krupinski EA, Schartz KM, van Tassell MS, Madsen MT, Caldwell RT, Berbaum KS. Effect of fatigue on reading computed tomography examination of the multiply injured patient. J Med Imaging. 2017;4:035504.
US Food and Drug Administration. Radiation-emitting products: frequently asked questions about MQSA. https://www.fda.gov/radiation-emitting-products/consumer-information-mqsa/frequently-asked-questions-about-mqsa.
US Food and Drug Administration. Mammography facility surveys, mammography equipment evaluations, and medical physicist qualification requirements under MQSA. Guidance document. Docket FDA-2009-D-0448. 13 Sept 2005.
US Food and Drug Administration. Display devices for diagnostic radiology – guidance for industry and Food and Drug Administration staff. 2 Oct 2017. https://www.fda.gov/media/95527/download.
Krupinski EA, Morgan MB, Siegel EL. ACR–AAPM–SIIM practice parameter for determinants of image quality in digital mammography.
Strudley CJ, Young KC, Warren LM. The role of imaging in screening special feature: full paper. Mammography cancer detection: comparison of single 8MP and pair of 5MP reporting monitors. Br J Radiol. 2018;91:20170246.
Krupinski EA. Diagnostic accuracy and visual search efficiency: single 8 MP vs. dual 5 MP displays. J Digit Imaging. 2017;30(2):144–7.
Yabuuchi H, Kawanami S, Kamitani T, Matsumura T, Yamasaki Y, Morishita J, Honda H. Detectability of BI-RADS category 3 or higher breast lesions and reading time on mammography: comparison between 5-MP and 8-MP LCD monitors. Acta Radiol. 2017;58(4):403–7.
Pisano ED, Gatsonis C, Hendrick E, Yaffe M, Baum JK, Acharyya S, Conant EF, Fajardo LL, Bassett L, D’Orsi C, Jong R. Diagnostic performance of digital versus film mammography for breast-cancer screening. N Engl J Med. 2005;353(17):1773–83.
Blume H. CRT-based display systems in radiology. In: SID symposium digest of technical papers, vol. 30, No. 1. Oxford: Blackwell Publishing Ltd; 1999. p. 968–71.
Bevins N, Flynn M, Silosky M, Marsh R, Walz-Flannigan A, Badano A. AAPM report 270: display quality assurance. American Association of Physicists in Medicine; 2019.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature
About this chapter
Cite this chapter
Krupinski, E.A., Storm, E.S. (2021). Viewing Images. In: Branstetter IV, B.F. (eds) Practical Imaging Informatics. Springer, New York, NY. https://doi.org/10.1007/978-1-0716-1756-4_17
Download citation
DOI: https://doi.org/10.1007/978-1-0716-1756-4_17
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-0716-1755-7
Online ISBN: 978-1-0716-1756-4
eBook Packages: MedicineMedicine (R0)