Antonuk, L.E., El-Mohri, Y., Siewerdsen, J.H., et al. (1997). Empirical investigation of the signal performance of a high-resolution, indirect detection, active matrix flat-panel imager (AMFPI) for fluoroscopic and radiographic operation. Med Phys, 24(1), 51–70.CrossRefGoogle ScholarPubMed

Antonuk, L.E., Jee, K.W., El-Mohri, Y., et al. (2000). Strategies to improve the signal and noise performance of active matrix, flat-panel imagers for diagnostic X-ray applications. Med Phys, 27(2), 289–306.CrossRefGoogle ScholarPubMed

Antonuk, L.E., Zhao, Q., Su, Z., et al. (2004). Systematic development of input-quantum-limited fluoroscopic imagers based on active-matrix flat-panel technology. Proc SPIE Med Imag, 5368, 127–138.CrossRefGoogle Scholar

Bachar, G., Siewerdsen, J.H., Daly, M.J., Jaffray, D.A., Irish, J.C. (2007). Image quality and localization accuracy in C-arm tomosynthesis-guided head and neck surgery. Med Phys, 34(12), 4664–4677.CrossRefGoogle ScholarPubMed

Badano, A., Kyprianou, I.S., Jennings, R.J., Sempau, J. (2007). Anisotropic imaging performance in breast tomosynthesis. Med Phys, 34(11), 4076–4091.CrossRefGoogle ScholarPubMed

Barten, P.G.J. (1999). Contrast Sensitivity of the Human Eye and its Effect on Image Quality. Bellingham, WA: SPIE Publications.Google Scholar

Bartling, S.H., Majdani, O., Gupta, R., et al. (2007). Large scan field, high spatial resolution flat-panel detector based volumetric CT of the whole human skull base and for maxillofacial imaging, Dentomaxillofac Radiol, 36(6), 317–327.CrossRefGoogle ScholarPubMed

Bissonnette, J.P., Cunningham, I.A., Jaffray, D.A., Fenster, A., Munro, P. (1997). A quantum accounting and detective quantum efficiency analysis for video-based portal imaging. Med Phys, 24(6), 815–826.CrossRefGoogle ScholarPubMed

Boone, J.M., Lindfors, K.K. (2006). Breast CT: potential for breast cancer screening and diagnosis. Future Oncol, 2(3), 351–356.CrossRefGoogle ScholarPubMed

Boone, J.M., Seibert, J.A. (1997). An accurate method for computer-generating tungsten anode X-ray spectra from 30 to 140 kV. Med Phys, 24(11), 1661–1670.CrossRefGoogle Scholar

Boyce, S.J., Chawla, A., Samei, E. (2005). Physical evaluation of a high frame rate, extended dynamic range flat panel detector for real-time cone beam computed tomography applications. Proc SPIE Med Imag, 5745, 591–598.Google Scholar

Burgess, A.E. (1994). Statistically defined backgrounds: performance of a modified nonprewhitening observer model. J Opt Soc Am A, 11(4), 1237–1242.CrossRefGoogle ScholarPubMed

Burgess, A.E., Jacobson, F.L., Judy, P.F. (2001). Human observer detection experiments with mammograms and power-law noise. Med Phys, 28(4), 419–437.Google Scholar

Bushberg, J.T., Seibert, J.A., Leidholdt, E.M., Boone, J.M. (2002). The Essential Physics of Medical Imaging. Hagerstown, MD: Lippincott Williams and Wilkins.Google Scholar

Cahn, R.N., Cederstrom, B., Danielsson, M., et al. (1999). Detective quantum efficiency dependence on X-ray energy weighting in mammography. Med Phys, 26(12), 2680–2683.CrossRefGoogle ScholarPubMed

Cunningham, I.A., Westmore, M.S., Fenster, A. (1994). A spatial-frequency dependent quantum accounting diagram and detective quantum efficiency model of signal and noise propagation in cascaded imaging systems. Med Phys, 21(3), 417–427.CrossRefGoogle ScholarPubMed

del Risco Norrlid, L., Edling, F., Fransson, K., et al. (2005). Simulation of the detective quantum efficiency for a hybrid pixel detector. Nucl Inst Meth Phys Res A, 543, 528–536.Google Scholar

Dobbins, J.T., III, Godfrey, D.J. (2003). Digital X-ray tomosynthesis: current state of the art and clinical potential. Phys Med Biol, 48(19), R65–R106.CrossRefGoogle ScholarPubMed

Fahrig, R., Holdsworth, D.W. (2000). Three-dimensional computed tomographic reconstruction using a C-arm mounted XRII: image-based correction of gantry motion nonidealities. Med Phys, 27 (1), 30–38.CrossRefGoogle ScholarPubMed

Feldkamp, L.A., Davis, L.C., Kress, J.W. (1984). Practical cone-beam algorithm. J Opt Soc Am A, 1, 612–619.CrossRefGoogle Scholar

Fewell, T.R., Shuping, R.E. (1977). Photon energy distribution of some typical diagnostic X-ray beams. Med Phys, 4(3), 187–197.Google Scholar

Fujita, H., Tsai, D., Itoh, T., et al. (1992). A simple method for determining the modulation transfer function in digital radiography. IEEE Trans Med Imag, 11(1), 34–39.Google Scholar

Gallas, B.D., Boswell, J.S., Badano, A., Gagne, R.M., Myers, K.J. (2004). An energy- and depth-dependent model for X-ray imaging. Med Phys, 31(11), 3132–3149.CrossRefGoogle ScholarPubMed

Ganguly, A., Rudin, S., Bednarek, D.R., Hoffmann, K.R. (2003). Micro-angiography for neuro-vascular imaging. II. Cascade model analysis. Med Phys, 30(11), 3029–3039.CrossRefGoogle ScholarPubMed

Hanson, K.M. (1979). Detectability in computed tomographic images. Med Phys, 6(5), 441–451.CrossRefGoogle ScholarPubMed

Hendee, W.R., Ritenour, E.R. (2002). Medical Imaging Physics, 4th ed. Hoboken, NJ: John Wiley.Google Scholar

Hunt, D.C., Kirby, S.S., Rowlands, J.A. (2002). X-ray imaging with amorphous selenium: X-ray to charge conversion gain and avalanche multiplication gain. Med Phys, 29(11), 2464–2471.Google Scholar

ICRU. (1996). ICRU Report 54. Medical Imaging – The Assessment of Image Quality. Bethesda, MD: International Commission on Radiation Units and Measurements.Google Scholar

IEC Committee 62B. (2003). IEC 62220–1 Medical Electrical Equipment Characteristics of Digital X-Ray Imaging Devices: Part 1. Determination of the Detective Quantum Efficiency. Geneva, Switzerland: IEC.Google Scholar

Jaffray, D.A., Siewerdsen, J.H., Wong, J.W., Martinez, A.A. (2002). Flat-panel cone-beam computed tomography for image-guided radiation therapy. Int J Radiat Oncol Biol Phys, 53(5), 1337–1349.Google Scholar

Jarry, G., Graham, S.A., Moseley, D.J., et al. (2006). Characterization of scattered radiation in kV CBCT images using Monte Carlo simulations. Med Phys, 33(11), 4320–4329.CrossRefGoogle ScholarPubMed

Johns, H.E., Cunningham, J.R. (1983). The Physics of Radiology, 4th ed. Springfield, IL: Charles C. Thomas.Google Scholar

Johns, P.C., Yaffe, M.J. (1985). Theoretical optimization of dual-energy X-ray imaging with application to mammography. Med Phys, 12(3), 289–296.Google Scholar

Kalender, W., Klotz, E., Kostaridou, L. (1988). An algorithm for noise suppression in dual-energy CT material density images. IEEE Trans Med Imag, 7, 218–224.CrossRefGoogle ScholarPubMed

Maidment, A.D.A., Ullberg, C., Lindman, K., et al. (2006). Evaluation of a photon-counting breast tomosynthesis imaging system. Proc SPIE Phys Med Imag, 6142, 61420B-1–61420B-11.Google Scholar

Metheany, K., Boone, J.M., Abbey, C.K., Packard, N. (2007). A comparison of anatomical noise properties between breast CT and projection breast imaging. Med Phys, 34(6), 2563.CrossRefGoogle Scholar

Metz, C.E. (1978). Basic principles of ROC analysis. Semin Nucl Med, 8(4), 283–298.Google Scholar

Nishikawa, R.M., Engstrom, E., Reiser, I. (2007). Comparison of the breast tissue power spectrum for mammograms, tomosynthesis projection images, and tomosynthesis reconstruction images. Annual Meeting of the Radiological Society of North America (RSNA).Google Scholar

Rafferty, E.A. (2007). Digital mammography: novel applications. Radiol Clin N Am, 45(5), 831–843, vii.CrossRefGoogle ScholarPubMed

Rafferty, M.A., Siewerdsen, J.H., Chan, Y., et al. (2006). Intraoperative cone-beam CT for guidance of temporal bone surgery. Otolaryngol Head Neck Surg, 134 (5), 801–808.CrossRefGoogle ScholarPubMed

Richard, S., Siewerdsen, J.H. (2007). Optimization of dual-energy imaging systems using generalized NEQ and imaging task. Med Phys, 34(1), 127–139.CrossRefGoogle ScholarPubMed

Richard, S., Siewerdsen, J.H., Jaffray, D., Moseley, D.J., Bakhtiar, B. (2005a). Generalized DQE analysis of radiographic and dual-energy imaging using flat-panel detectors. Med Phys, 32, 1397–1413.CrossRefGoogle ScholarPubMed

Richard, S., Siewerdsen, J.H., Jaffray, D.A., Moseley, D.J., Bakhtiar, B. (2005b). Generalized DQE analysis of dual-energy imaging using flat-panel detectors. Proc SPIE Phys Med Imag, 5745, 519–528.CrossRefGoogle Scholar

Riederer, S.J., Pelc, N.J., Chesler, D.A. (1978). The noise power spectrum in computed X-ray tomography. Phys Med Biol, 23(3), 446–454.CrossRefGoogle ScholarPubMed

Roehrig, H., Fajardo, L.L., Yu, T., Schempp, W.S. (1994). Signal, noise and detective quantum efficiency in CCD based X-ray imaging systems for use in mammography. Proc SPIE Phys Med Imag, 2163, 320–332.CrossRefGoogle Scholar

Rose, A. (1948). The sensitivity performance of the human eye on an absolute scale. J Opt Soc Am, 38, 196–208.Google Scholar

Rowlands, J.A. (1996). Digital X-ray systems based on amorphous selenium. AJR Am J Roentgenol, 167(2), 409–411.Google Scholar

Sawant, A., Antonuk, L.E., El-Mohri, Y., et al. (2006). Segmented crystalline scintillators: empirical and theoretical investigation of a high quantum efficiency EPID based on an initial engineering prototype CsI(Tl) detector. Med Phys, 33, 1053–1066.Google Scholar

Shkumat, N.A., Siewerdsen, J.H., Dhanantwari, A.C., et al. (2007). Optimization of image acquisition techniques for dual-energy imaging of the chest. Med Phys, 34(10), 586–601.Google Scholar

Siewerdsen, J.H., Antonuk, L.E. (1998). DQE and system optimization for indirect-detection flat-panel imagers in diagnostic radiology. Proc SPIE Phys Med Imag, 3336, 546–555.CrossRefGoogle Scholar

Siewerdsen, J.H., Jaffray, D.A. (2000a). Cone-beam CT with a flat-panel imager: noise considerations for fully 3D computed tomography. Proc SPIE Phys Med Imag, 3977, 408–416.CrossRefGoogle Scholar

Siewerdsen, J.H., Jaffray, D.A. (2000b). Optimization of X-ray imaging geometry (with specific application to flat-panel cone-beam computed tomography). Med Phys, 27(8), 1903–1914.Google Scholar

Siewerdsen, J.H., Jaffray, D.A. (2001). Cone-beam computed tomography with a flat-panel imager: magnitude and effects of X-ray scatter. Med Phys, 28(2), 220–231.CrossRefGoogle ScholarPubMed

Siewerdsen, J.H., Jaffray, D.A. (2003). Three-dimensional NEQ transfer characteristics of volume CT using direct and indirect-detection flat-panel imagers. Proc SPIE Phys Med Imag, 29(11), 2655–2671.Google Scholar

Siewerdsen, J.H., Antonuk, L.E., El-Mohri, Y., et al. (1997). Empirical and theoretical investigation of the noise performance of indirect detection, active matrix flat-panel imagers (AMFPIs) for diagnostic radiology. Med Phys, 24(1), 71–89.CrossRefGoogle ScholarPubMed

Siewerdsen, J.H., Moseley, D.J., Bakhtiar, B., Richard, S., Jaffray, D.A. (2004a). The influence of antiscatter grids on soft-tissue detectability in cone-beam computed tomography with flat-panel detectors. Med Phys, 31(12), 3506–3520.CrossRefGoogle ScholarPubMed

Siewerdsen, J.H., Moseley, D.J., Jaffray, D.A. (2004b). Incorporation of task in 3D imaging performance evaluation: the impact of asymmetric NPS on detectability. Proc SPIE Phys Med Imag, 5368, 89–97.CrossRefGoogle Scholar

Siewerdsen, J.H., Waese, A.M., Moseley, D.J., Richard, S., Jaffray, D.A. (2004c). Spektr: a computational tool for X-ray spectral analysis and imaging system optimization. Med Phys, 31(11), 3057–3067.Google Scholar

Siewerdsen, J.H., Moseley, D.J., Burch, S., et al. (2005). Volume CT with a flat-panel detector on a mobile, isocentric C-arm: pre-clinical investigation in guidance of minimally invasive surgery. Med Phys, 32(1), 241–254.CrossRefGoogle ScholarPubMed

Silverman, J.D., Paul, N.S., Siewerdsen, J.H. (2009). Investigation of lung nodule detectability in low-dose 320-slice computed tomography. Med Phys, 26, 1700–1710.Google Scholar

Spies, L., Ebert, M., Groh, B.A., Hesse, B.M., Bortfeld, T. (2001). Correction of scatter in megavoltage cone-beam CT. Phys Med Biol, 46(3), 821–833.CrossRefGoogle ScholarPubMed

Swank, R.K. (1973). Absorption and noise in X-ray phosphors. J Appl Phys, 44(9), 4199–4203.Google Scholar

Tucker, D.M., Barnes, G.T., Chakraborty, D.P. (1991). Semiempirical model for generating tungsten target X-ray spectra. Med Phys, 18(2), 211–218.CrossRefGoogle ScholarPubMed

Tutar, I.B., Managuli, R., Shamdasani, V., et al. (2003). Tomosynthesis-based localization of radioactive seeds in prostate brachytherapy. Med Phys, 30(12), 3135–3142.CrossRefGoogle ScholarPubMed

Vedantham, S., Karellas, A., Suryanarayanan, S. (2004). Solid-state fluoroscopic imager for high-resolution angiography: parallel-cascaded linear systems analysis. Med Phys, 31(5), 1258–1268.CrossRefGoogle ScholarPubMed

Warp, R.J., Dobbins, J.T., III. (2003). Quantitative evaluation of noise reduction strategies in dual-energy imaging. Med Phys, 30(2), 190–198.CrossRefGoogle ScholarPubMed

Yao, J., Cunningham, I.A. (2001). Parallel cascades: new ways to describe noise transfer in medical imaging systems. Med Phys, 28(10), 2020–2038.CrossRefGoogle ScholarPubMed

Zhao, W., Rowlands, J.A. (1997). Digital radiology using active matrix readout of amorphous selenium: theoretical analysis of detective quantum efficiency. Med Phys, 24(12), 1819–1833.Google Scholar

ACR. (2017). ACR-AAPM-SIIM technical standard for electronic pratice of medical imaging. www.acr.org/~/media/ACR/Documents/PGTS/standards/ElectronicPracticeMedImg.pdf (accessed October 12, 2017).Google Scholar

Badano, A. (2009). Effect of slow display on detectabilty when browsing large image datasets. J Soc Inform Display, 17(11), 891–896.Google Scholar

Badano, A., Fifadara, D. (2004). Goniometric and conoscopic measurements of angular AMLCD contrast. Med Phys, 31(12), 3452–3460.Google Scholar

Badano, A., Wang, J., Boynton, P., et al. (2016). Technical note: gray tracking in medical color displays – a report of task group 196. Med Phys, 43(7), 4017–4022.CrossRefGoogle ScholarPubMed

Barten, P.G.J. (2009). Contrast Sensitivity of the Human Eye and its Effects on Image Quality. Bellingham, WA: SPIE Press.Google Scholar

Bevins, N., Flynn, M., Silosky, M. et al. (2018). Display quality assurance: a report of AAPM task group 270. (anticipated release late 2018).Google Scholar

Born, M., Wolf, E. (1999). Principles of Optics: Electromagnetic Theory of Propagation, Interference and Diffraction of Light. London: Cambridge University Press.CrossRefGoogle Scholar

Bushberg, J.T. (2012). The Essential Physics of Medical Imaging. Philadelphia, PA: Wolters Kluwer Health/Lippincott Williams and Wilkins.Google Scholar

CIE. (2004). International Commission on Illumination. CIE 15:2004: Colorimetry. 3rd edition. Available at: www.cie.co.at/publ/abst/15-2004.html.Google Scholar

Eizo. (2015). Advantages of anti reflection (AR) treatment. Eizo white paper, 14-002 revision A, Q15B014-AS-10001. Available at: www.eizoglobal.com/support/db/files/technical_information/WP14-002.pdf (accessed January 4, 2018).Google Scholar

Elze, T., Tanner, T.G. (2012). Temporal properties of liquid crystal displays: implications for vision science experiments. PLoS One, 7, e44048.Google Scholar

Elze, T., Taylor, C., Bex, P.J. (2013). An evaluation of organic light emitting diode monitors for medical applications: great timing, but luminance artifacts. Med Phys, 40 (9), 092701.CrossRefGoogle ScholarPubMed

Flynn, M. (2013). mRGB: AAPM TG196 progress. 2013 ICC Meeting, Medical Imaging Working Group, Vancouver, BC. Available at: www.color.org/groups/medical/Flynn.pdf (accessed October 14, 2017).Google Scholar

Hsieh, D. (2016). Oxide is the most cost-effective TFT LCD display technology for tablet PCs. Available at: http://blog.ihs.com/oxide-is-the-most-cost-effective-tft-lcd-display-technology-for-tablet-pcs (accessed January 4, 2018).Google Scholar

ICC. (2016). Visualization of medical content on color display systems. ICC white paper, 44. Available at: www.color.org/whitepapers/ICC_White_Paper44_Visualization_of_colour_on_medical_displays.pdf (accessed January 4, 2018).Google Scholar

IEC. (1999). IEC 61966-2-1 Multimedia systems and equipment – colour measurement and management – part 2-1: colour management – default RGB colour space – sRGB. Available at: https://webstore.iec.ch/publication/6169#additionalinfo,Google Scholar

IEC. (2013). IEC 62341-5-3:2013 Organic light emitting diode (OLED) displays – part 5-3: measuring methods of image sticking and lifetime. Available at: https://webstore.iec.ch/publication/6878.Google Scholar

IEC. (2017). IEC 62341-6-1:2017. Organic light emitting diode (OLED) displays – part 6-1: measuring methods of optical and electro-optical parameters. Available at: https://webstore.iec.ch/publication/28881.Google Scholar

Kimpe, T., Xthona, A., Matthijs, P., De Paepe, L. (2005). Solution for nonuniformities and spatial noise in medical LCD displays by using pixel-based correction. J Digit Imag, 18(3), 209–218.Google Scholar

Lee, J.-H., Ho, Y.-H., Chen, K.-Y., et al. (2008). Efficiency improvement and image quality of organic light-emitting display by attaching cylindrical microlens arrays. Opt Exp, 16(26), 21184–21190.Google Scholar

Mertens, R. (2017). Sony may be JOLED’s first customer for its 21.6″ 4K medical OLED monitors. Available at: www.oled-info.com/sony-may-be-joleds-first-customer-its-216-4k-medical-oled-monitors (accessed January 4, 2018).Google Scholar

Okutani, S., Kobayashi, M., Ibaraki, N. (2006). Quantitative evaluation of display characteristics of AMOLED displays. J Soc Inform Display, 14(12), 1119–1125.CrossRefGoogle Scholar

Ruuge, A., Mahmood, U., Erdi, Y. E. (2016) The assessment and characterization of the built-in internal photometer of primary diagnostic monitors. J Appl Clin Med Phys, 18(2), 170–175.Google Scholar

Samei, E., Badano, A., Chakraborty, D., et al. (2005). Assessment of display performance for medical imaging systems. Online only report no. OR03 – report of AAPM task group 18, 2005. Available at: www.aapm.org/pubs/reports/OR_03.pdf (accessed January 4, 2018).Google Scholar

Silosky, M., Marsh, R.M. (2013). Constancy of built-in luminance meter measurements in diagnostic displays. Med Phys, 40(12), 121902.CrossRefGoogle ScholarPubMed

Walz-Flannigan, A., Stekel, S., Weber, H., et al. (2011) Aging and quality control of color LCDs for radiologic imaging. J Digit Imag, 24(5): 828–832.CrossRefGoogle ScholarPubMed

Yamazaki, A. (2013). image quality characteristics of handheld display devices for medical imaging. PLoS One, 8, e79243.CrossRefGoogle ScholarPubMed

Abboud, S., Weiss, F., Siegel, E., Jeudy, J. (2013). TB or not TB: interreader and intrareader variability in screening diagnosis on an iPad versus a traditional display. J Am Coll Radiol, 10(1), 42–44.Google Scholar

Abdullah, B.J., Ng, K.H. (2001). In the eyes of the beholder: what we see is not what we get. Br J Radiol, 74(884), 675–676.CrossRefGoogle Scholar

ACR. (1999). ACR Mammography Quality Control Manual. Reston, VA: ACR. Available at: www.acraccreditation.org/~/media/ACRAccreditation/Documents/Mammography/Clinical_Image_SECTION_1999MammoQC.pdf?la=en (accessed January 8, 2018).Google Scholar

ACR. (2001). ACR Practice Guideline for the Performance of Whole Breast Digital Mammography (Res. 7). Reston, VA: ACR.Google Scholar

Ardito, M. (1994). Studies of the influence of display size and picture brightness on the preferred viewing distance for HDTV programs. SMPTE J, 103(8), 517–522.CrossRefGoogle Scholar

Badano, A. (2017). Considerations for the use of handheld image viewers: a report of AAPM task group 260. In: Chen, P.H., Prevedello, L.M.S. (eds.) SIIM 2017 Scientific Session Productivity and Workflow. Pittsburg, PA: SIIM, pp. 1–2.Google Scholar

Badano, A., Flynn, M.J., Kanicki, J. (2004). High-Fidelity Medical Imaging Displays (Vol. 63). Bellingham, WA: SPIE Press, pp. 10–11.Google Scholar

Barco, . (2017). Coronis Fusion 10MP. Available at: www.barco.com/en/Products/Displays-monitors-workstations/Medical-displays/Diagnostic-displays/10-MegaPixel-wide-screen-diagnostic-grayscale-display-system.aspx (accessed January 8, 2018).Google Scholar

Barten, P.G. (1999). Contrast Sensitivity of the Human Eye and its Effects on Image Quality (Vol. 72). Bellingham, WA: SPIE Press.CrossRefGoogle Scholar

Berglund, B., Lindvall, T., Schwela, D.H. (2000). New WHO guidelines for community noise. Noise Vibrat Worldwide, 31(4), 24–29.Google Scholar

Bessho, Y., Yamaguchi, M., Fujita, H., Azuma, M. (2009). Usefulness of reduced image display size in softcopy reading. Acad Radiol, 16(8), 940–946.CrossRefGoogle ScholarPubMed

Bevins, N.B., Flynn, M.J., Silosky, M.S., Walz-Flannigan, A.I. (2017). Display quality assurance: a report of AAPM task group 270. AAPM. Available at: www.aapm.org/eval/m/Quiz.aspx?sid=7117&mid=127 (accessed January 8, 2018).Google Scholar

Bick, U., Diekmann, F. (2010). Digital Mammography. Heidelberg, Germany: Springer Science and Business Media.Google Scholar

Boonn, W.W., Flanders, A.E. (2005). Informatics in radiology (infoRAD): survey of personal digital assistant use in radiology. Radiographics, 25(2), 537–541.CrossRefGoogle ScholarPubMed

Brennan, P.C., McEntee, M., Evanoff, M., Phillips, P., O’Connor, W.T., Manning, D.J. (2007). Ambient lighting: effect of illumination on soft-copy viewing of radiographs of the wrist. AJR, 188(2), W177–W180.CrossRefGoogle ScholarPubMed

Brennan, P.C., Ryan, J., Evanoff, M., Toomey, R.J., O’Beirne, A., Manning, D., McEntee, M. (2008). The impact of acoustic noise found within clinical departments on radiology performance. Acad Radiol, 15(4), 472–476.CrossRefGoogle ScholarPubMed

Broadbent, D.E. (1958). Perception and Communication. Oxford, England: Pergamon Press.CrossRefGoogle Scholar

Burkitt, H.G., Young, B., Heath, J.W. (1994). Wheater’s Functional Histology – A Text and Colour Atlas, 3rd ed. Edinburgh: Churchill Livingstone, pp. 376–386.Google Scholar

Butler, M.L., Lowe, J., Toomey, R.J., Maher, M., Evanoff, M.E., Rainford, L. (2013). The effect of viewing distance on observer performance in skeletal radiographs. In: SPIE Medical Imaging. Bellingham, WA: International Society for Optics and Photonics, pp. 867315–867315.Google Scholar

Carmichael, J.H.E., Maccia, C., Moores, B.M., Oestmann, J.W., Schibilla, H., Teunen, D., et al. (1996). European Guidelines on Quality Criteria for Diagnostic Radiographic Images. Luxembourg: ECSC-EC-EAEC.Google Scholar

CCOHS. (2017). OSH answers fact sheets. Available at: www.ccohs.ca/oshanswers/phys_agents/max_temp.html (accessed January 8, 2018).Google Scholar

Chawla, A.S., Samei, E. (2007). Ambient illumination revisited: a new adaptation-based approach for optimizing medical imaging reading environments. Med Phys, 34(1), 81–90.CrossRefGoogle ScholarPubMed

Choudhri, A.F., Carr, T.M., 3rd, Ho, C.P., Stone, J.R., Gay, S.B., Lambert, D.L. (2012). Handheld device review of abdominal CT for the evaluation of acute appendicitis. J Digit Imag, 25(4), 492–496.CrossRefGoogle ScholarPubMed

Darbyshire, J.L., Young, J.D. (2013). An investigation of sound levels on intensive care units with reference to the WHO guidelines. Crit Care, 17(5), R187.CrossRefGoogle Scholar

Dasgupta, S., Wheeler, D., Huq, M., Khaliquzzaman, M. (2009). Improving indoor air quality for poor families: a controlled experiment in Bangladesh. Indoor Air, 19(1), 22–32.Google Scholar

Dreyer, K.J., Hirschhorn, D.S., Thrall, J.H., PACS, M. (2006). A Guide to the Digital Revolution. New York: Springer.Google Scholar

Ekpo, E.U., McEntee, M.F. (2015). An evaluation of performance characteristics of primary display devices. J Digit Imag, 29(2), 175–182.CrossRefGoogle Scholar

Emoto, M., Sugawara, M. (2016). Viewers’ optimization of preferred viewing distance by spatial resolution of TV display. Displays, 45, 1–5.CrossRefGoogle Scholar

Emoto, M., Sugawara, M., Nojiri, Y. (2008). Viewing angle dependency of visually-induced motion sickness in viewing wide-field images by subjective and autonomic nervous indices. Displays, 29(2), 90–99.CrossRefGoogle Scholar

European Commission. Directorate-General for Environment, Nuclear Safety, and Civil Protection, and European Commission. (1997). Radiation protection 91: criteria for acceptability of radiological (including radiotherapy) and nuclear medicine installations. Available at: https://ec.europa.eu/energy/en/radiation-protection-publications.Google Scholar

Fisher, P.D., Brauer, G.W. (1989). Impact of image size on effectiveness of digital imaging systems. J Digit Imag, 2(1), 39–41.CrossRefGoogle ScholarPubMed

Flynn, M.J., Kanicki, J., Badano, A., Eyler, W.R. (1999). High-fidelity electronic display of digital radiographs. Radiographics, 19(6), 1653–1669.CrossRefGoogle ScholarPubMed

Fuchsjäger, M.H., Schaefer-Prokop, C.M., Eisenhuber, E., Homolka, P., Weber, M., Funovics, M.A., Prokop, M. (2003). Impact of ambient light and window settings on the detectability of catheters on soft-copy display of chest radiographs at bedside. AJR, 181(5), 1415–1421.Google Scholar

Fujita, H., Kuwahata, N., Hattori, H., Kinoshita, H., Fukuda, H. (2016). Investigation of optimal display size for viewing T1-weighted MR images of the brain using a digital contrast-detail phantom. J Appl Clin Med Phys, 17(1), 353–359.Google Scholar

Geller, J. (2014). Food and Drug Administration issues final guidance on mobile medical applications. J Clin Eng, 39(1), 4–7.CrossRefGoogle Scholar

Gregory, R.L. (1998). Eye and Brain: The Psychology of Seeing (5th ed.) Oxford: Oxford University Press, p, 55.Google Scholar

Gur, D., Klym, A.H., King, J.L., Maitz, G.S., Mello-Thoms, C., Rockette, H.E., Thaete, F.L. (2006). The effect of image display size on observer performance an assessment of variance components. Acad Radiol, 13(4), 409–413.CrossRefGoogle ScholarPubMed

Harisinghani, M.G., Blake, M.A., Saksena, M., Hahn, P.F., Gervais, D., Zalis, M., et al. (2004). Importance and effects of altered workplace ergonomics in modern radiology suites. Radiographics, 24(2), 615–627.Google Scholar

Hirschorn, D.S., Krupinski, E.A., Flynn, M.J. (2014). PACS displays: how to select the right display technology. J Am Coll Radiol, 11(12), 1270–1276.Google Scholar

Ichinohe, K., Takahashi, M., Tooyama, N. (2003). Treatment delay and radiological errors in patients with bone metastases. Braz J Med Biol Res, 36(10), 1419–1424.CrossRefGoogle ScholarPubMed

Jaschtnski-Kruza, W. (1990). On the preferred viewing distances to screen and document at VDU workplaces. Ergonomics, 33(8), 1055–1063.Google Scholar

John, S., Poh, A.C.C., Lim, T.C.C., Chan, E.H.Y., Chong, L.R. (2012). The iPad tablet computer for mobile on-call radiology diagnosis? Auditing discrepancy in CT and MRI reporting. J Digit Imag 25(5), 628–634.CrossRefGoogle ScholarPubMed

Kalyanpur, A., Panughpath, S. (2012). Radiology and the mobile device: radiology in motion. Ind J Radiol Imag, 22(4), 246.Google Scholar

Kanal, K.M., Krupinski, E., Berns, E.A., Geiser, W.R., Karellas, A., Mainiero, M.B., et al. (2012). ACR–AAPM–SIIM practice guideline for determinants of image quality in digital mammography. J Digit Imag, 26(1), 10–25.CrossRefGoogle Scholar

Kelsey, C.A., Moseley, R.D., Jr, Mettler, F.A., Jr, Briscoe, D.E. (1981). Observer performance as a function of viewing distance. Invest Radiol, 16(5), 435–437.CrossRefGoogle ScholarPubMed

Khademi, G., Roudi, M., Shah Farhat, A., Shahabian, M. (2011). Noise pollution in intensive care units and emergency wards. Iran J Otorhinolaryngol, 23(65), 141–148.Google Scholar

Kim, J.-P., Kim, J.-P., Kim, D.H., Kim, S.-J. (2005). Design of software architecture for mobile devices supporting interworking between CDMA and WiBro. In The 7th International Conference on Advanced Communication Technology, 2005, ICACT 2005. Available at: https://doi.org/10.1109/icact.2005.246003 (accessed January 8, 2018).Google Scholar

Kim, Y.S.K., Park, J. J., Kim, S.H. (2007). PDA-phone-based instant transmission of radiological images over a CDMA network by combining the PACS screen with a Bluetooth-interfaced local wireless link. J Digit Imag, 20(2), 131–139.CrossRefGoogle Scholar

Kim, C.J.-W., Lee, S.-S., Huh, K.-H., Yi, W.-J., Heo, M.-S., Choi, S.-C. (2011). Effect of LCD monitor type and observer experience on diagnostic performance in soft-copy interpretations of the maxillary sinus on panoramic radiographs. Imag Sci Dent, 41(1), 11–16.CrossRefGoogle ScholarPubMed

Kim, C., Kang, B., Choi, H.J., Park, J.B. (2015). A feasibility study of real-time remote CT reading for suspected acute appendicitis using an iPhone. J Digit Imag, 28(4), 399–406.Google Scholar

Krupinski, E.A. (2000). Practical applications of perceptual research. In: Beutel, J., Kundel, H.L., Van Metter, R.L. (eds.) Handbook of Medical Imaging: Physics and Psychophysics. Bellingham, WA: SPIE, p. 905.Google Scholar

Krupinski, E.A. (2014). Human factors and human-computer considerations in teleradiology and telepathology. Healthcare (Basel, Switz), 2(1), 94–114.Google Scholar

Lee, K.S. (2005). Ergonomics in total quality management: how can we sell ergonomics to management? Ergonomics, 48(5), 547–558.Google ScholarPubMed

Liukkonen, E., Jartti, A., Haapea, M., Oikarinen, H., Ahvenjärvi, L., Mattila, S., et al. (2016). Effect of display type and room illuminance in chest radiographs. Eur Radiol, 26(9), 3171–3179.CrossRefGoogle ScholarPubMed

Marchand, G.C., Nardi, N.M., Reynolds, D., Pamoukov, S. (2014). The impact of the classroom built environment on student perceptions and learning. J Environ Psychol, 40, 187–197.Google Scholar

Mazer, S.E. (2005). Hear, hear. Assessing and resolving hospital noise issues. Health Facil Manage, 18(4), 24–29.Google ScholarPubMed

McEntee, M., Gafoor, S. (2009). Ambient temperature variation affects radiological diagnostic performance. In: SPIE Medical Imaging. Bellingham, WA: International Society for Optics and Photonics, pp. 72631H–72631H.Google Scholar

McLeod, T.G., Ebbert, J.O., Lymp, J.F. (2003). Survey assessment of personal digital assistant use among trainees and attending physicians. JAMIA, 10(6), 605–607.Google Scholar

McNulty, J.P., Ryan, J.T., Evanoff, M.G., Rainford, L.A. (2012). Flexible image evaluation: iPad versus secondary-class monitors for review of MR spinal emergency cases, a comparative study. Acad Radiol, 19(8), 1023–1028.CrossRefGoogle ScholarPubMed

National Electrical Manufacturers Association. (2007). Digital Imaging and Communications in Medicine (DICOM) Part 14: Grayscale Display Standard Function. Rosslyn, VA: National Electrical Manufacturers Association (NEMA).Google Scholar

Norweck, J.T., Anthony Seibert, J., Andriole, K.P., Clunie, D.A., Curran, B.H., Flynn, M.J., et al. (2013). ACR–AAPM–SIIM technical standard for electronic practice of medical imaging. J Digit Imag, 26(1), 38–52.CrossRefGoogle ScholarPubMed

O’Shea, R.P. (1991). Thumb’s rule tested: visual angle of thumb’s width is about 2 deg. Perception, 20(3), 415–418.Google Scholar

Pollard, B.J., Chawla, A.S., Delong, D.M., Hashimoto, N., Samei, E. (2008). Object detectability at increased ambient lighting conditions. Med Phys, 35(6), 2204–2213.Google Scholar

Pollard, B.J., Samei, E., Chawla, A.S., Baker, J., Ghate, S., Kim, C., et al. (2009). The influence of increased ambient lighting on mass detection in mammograms. Acad Radiol, 16(3), 299–304.Google Scholar

Prabhu, S.P., Gandhi, S., Goddard, P.R. (2005). Ergonomics of digital imaging. Br J Radiol, 78(931), 582–586.CrossRefGoogle ScholarPubMed

Reiner, B.I., Siegel, E.L. (2006). PACS and productivity. In: Filmless Radiology pp. 103–112. Heidelberg, Germany: Springer.Google Scholar

Riccò, M., Cattani, S., Gualerzi, G., Signorelli, C. (2016). Work with visual display units and musculoskeletal disorders: a cross-sectional study. Medycyna Pracy, 67(6), 707–719.Google Scholar

Rodrigues, M.A., Visvanathan, A., Murchison, J.T., Brady, R.R. (2013). Radiology smartphone applications; current provision and cautions. Insights Imag, 4(5), 555–562.Google Scholar

Samei, E., Badano, A., Chakraborty, D., Compton, K. (2005a). Assessment of Display Performance for Medical Imaging Systems, Report of the American Association of Physicists in Medicine (AAPM) Task Group 18. Bellingham, WA: AAPM.Google Scholar

Samei, E., Badano, A., Chakraborty, D., Compton, K., Cornelius, C., Corrigan, K., et al. (2005b). Assessment of display performance for medical imaging systems: executive summary of AAPM TG18 report. Med Phys, 32(4), 1205–1225.CrossRefGoogle ScholarPubMed

Schaefer, C.M., Greene, R., Oestmann, J.W., Hall, D.A., Llewellyn, H.J., McCarthy, K.A., et al. (1990). Digital storage phosphor imaging versus conventional film radiography in CT-documented chest disease. Radiology, 174(1), 207–210.Google ScholarPubMed

Schlechtweg, P.M., Kammerer, F.J., Seuss, H., Uder, M., Hammon, M. (2016). Mobile image interpretation: diagnostic performance of CT exams displayed on a tablet computer+ in detecting abdominopelvic hemorrhage. J Digit Imag, 29(2), 183–188.Google ScholarPubMed

Schwela, D.H. (2001). The new World Health Organization guidelines for community noise. Noise Control Eng J, 49(4), 193.CrossRefGoogle Scholar

Sekuler, R., Blake, R. (1994). Perception. New York, NY: McGraw-Hill.Google Scholar

Seltzer, S.E., Saini, S., Bramson, R.T., Kelly, P., Levine, L., Chiango, B.F., et al. (1998). Can academic radiology departments become more efficient and cost less? Radiology, 209(2), 405–410.CrossRefGoogle ScholarPubMed

Sharpe, E.E., 3rd, Kendrick, M., Strickland, C., Dodd, G.D., 3rd. (2013). The radiology resident iPad toolbox: an educational and clinical tool for radiology residents. J Am Coll Radiol, 10(7), 527–532.CrossRefGoogle ScholarPubMed

Shintaku, W.H., Scarbecz, M., Venturin, J.S. (2012). Evaluation of interproximal caries using the IPad 2 and a liquid crystal display monitor. Oral Surg Oral Med Oral Pathol Oral Radiol Endod, 113(5), e40–e44.Google Scholar

Siegel, L. (1962). Fatigue and boredom. In: Siegel, L. (ed.) Industrial Psychology. Washington, DC: American Psychological Association, pp. 193–209.Google Scholar

Siegel, R.B., Abiri, M., Chacko, A., Morin, R., Ro, D.W., et al. (2000). The filmless radiology reading room: a survey of established picture archiving and communication system sites. J Digit Imag, 13(S1), 22–23.Google Scholar

Straub, W.H., Gur, D., Good, W.F., Campbell, W.L., Davis, P.L., Hecht, S.T., et al. (1991). Primary CT diagnosis of abdominal masses in a PACS environment. Radiology, 178(3), 739–743.CrossRefGoogle Scholar

Sund, P., Båth, M., Månsson, L. G. (2008). Detection of low contrast test patterns on an LCD with different luminance and illuminance settings. Proc SPIE, 6917, 69170N.Google Scholar

Tewes, S., Rodt, T., Marquardt, S., Evangelidou, E., Wacker, F.K., von Falck, C. (2013). Evaluation of the use of a tablet computer with a high-resolution display for interpreting emergency CT scans. Rofo, 185(11), 1063–1069.Google ScholarPubMed

Thomas, J.A., Chakrabarti, K., Kaczmarek, R.V., Maslennikov, A., Mitchell, C.A., Romanyukha, A. (2006). Optimization of reading conditions for flat panel displays. J Digit Imag, 19(2), 181–187.Google Scholar

Uffmann, M., Prokop, M., Kupper, W., Mang, T., Fiedler, V., Schaefer-Prokop, C. (2005). Soft-copy reading of digital chest radiographs: effect of ambient light and automatic optimization of monitor luminance. Invest Radiol, 40(3), 180–185.CrossRefGoogle ScholarPubMed

Venjakob, A.C., Marnitz, T., Phillips, P., Mello-Thoms, C.R. (2016). Image size influences visual search and perception of hemorrhages when reading cranial CT: an eye-tracking study. Hum Factors, 58(3), 441–451.CrossRefGoogle ScholarPubMed

WHO. (1982). Quality assurance in diagnostic radiology. Available at: http://apps.who.int/iris/bitstream/10665/39095/1/9241541644.pdf (accessed January 8, 2018).Google Scholar

Witterseh, T., Wyon, D.P., Clausen, G. (2004). The effects of moderate heat stress and open-plan office noise distraction on SBS symptoms and on the performance of office work. Indoor Air, 14 Suppl 8, 30–40.CrossRefGoogle ScholarPubMed

Wyon, D.P., Wargocki, P. (2013). Room Temperature Effects on Office Work. London: Taylor & Francis, pp. 181–192.Google Scholar

Yamaguchi, M., Fujita, H., Bessho, Y., Inoue, T., Asai, Y., Murase, K. (2011). Investigation of optimal display size for detecting ground-glass opacity on high resolution computed tomography using a new digital contrast-detail phantom. Eur J Radiol, 80(3), 845–850.CrossRefGoogle ScholarPubMed

Yamazaki, A., Liu, P., Cheng, W.-C., Badano, A. (2013). Image quality characteristics of handheld display devices for medical imaging. PLoS One, 8(11), e79243.CrossRefGoogle ScholarPubMed

Zwart, C.M., He, M., Wu, T., Demaerschalk, B.M., Mitchell, J.R., Hara, A.K. (2015). Selection and pilot implementation of a mobile image viewer: a case study. JMIR mHealth and uHealth, 3(2), e45.CrossRefGoogle ScholarPubMed

ACR. (2017). What is a radiologist? Available at: www.acr.org/Quality-Safety/Radiology-Safety/Patient-Resources/About-Radiology (accessed March 29, 2017).Google Scholar

Allerton, D.J. (2010). The impact of flight simulation in aerospace. Aeronaut J, 114(1162), 747–756.Google Scholar

Auffermann, W.F., Henry, T.S., Little, B.P., Tigges, S., Tridandapani, S. (2015). Simulation for teaching and assessment of nodule perception on chest radiography in nonradiology health care trainees. J Am Coll Radiol, 12(11), 1215–1222.Google Scholar

Auffermann, W.F., Little, B.P., Tridandapani, S. (2016). Teaching search patterns to medical trainees in an educational laboratory to improve perception of pulmonary nodules. J Med Imag, 3(1), 011006.Google Scholar

Baker, J.A., Kornguth, P.J., Floyd, C.E., Jr (1996). Breast imaging reporting and data system standardized mammography lexicon: observer variability in lesion description. AJR. Am J Roentgenol, 166(4), 773–778.Google ScholarPubMed

Bjork, R.A. (1994). Memory and metamemory considerations in the training of human beings. In: Metcalfe, J., Shimamura, A. (eds.) Metacognition: Knowing about Knowing. Cambridge, MA: MIT Press.Google Scholar

Boeing., (2017). Statistical Summary of Commercial Jet Airplane Accidents, 1959–2016. Aviation Safety. Seattle, WA: Boeing Commercial Airplanes.Google Scholar

Bradley, A.P. (1997). The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recogn, 30(7), 1145–1159.CrossRefGoogle Scholar

Brusilovsky, P., Millán, E. (2007). User models for adaptive hypermedia and adaptive educational systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web. Lecture Notes in Computer Science, vol. 4321. Berlin: Springer-Verlag, pp. 3–53.Google Scholar

Buckle, C.E., Udawatta, V., Straus, C.M. (2013). Now you see it, now you don’t: visual illusions in radiology. Radiographics, 33(7), 2087–2102.CrossRefGoogle ScholarPubMed

Chasen, M.H. (2001). Practical applications of Mach band theory in thoracic analysis. Radiology, 219(3), 596–610.Google Scholar

Desser, T.S. (2007). Simulation-based training: the next revolution in radiology education? J Am Coll Radiol, 4(11), 816–824.Google Scholar

Dictionary.com. (2017). Intern–2. Available at: www.dictionary.com/browse/intern.Google Scholar

Franklin, B. (2017). Benjamin Franklin quotes. Available at: www.brainyquote.com/quotes/quotes/b/benjaminfr383997.html.Google Scholar

Goodman, L. (2014). Felson's Principles of Chest Roentgenology. Philadelphia, PA: Saunders.Google Scholar

Grimm, L.J., Ghate, S.V., Yoon, S.C., Kuzmiak, C.M., Kim, C., Mazurowski, M.A. (2014a). Predicting error in detecting mammographic masses among radiology trainees using statistical models based on BI-RADS features. Med Phys, 41(3), 31909-31909.CrossRefGoogle ScholarPubMed

Grimm, L.J., Kuzmiak, C.M., Ghate, S.V., Yoon, S.C., Mazurowski, M.A. (2014b). Radiology resident mammography training: interpretation difficulty and error-making patterns. Acad Radiol, 21(7), 888–892.Google Scholar

Grimm, L.J., Zhang, J., Lo, J.Y., Johnson, K., Ghate, S.V., Mazurowski, M.A. (2016). Radiology trainee performance in digital breast tomosynthesis: relationship between difficulty and error making patterns. J Am Coll Radiol, 13(2), 198–202.CrossRefGoogle ScholarPubMed

Kundel, H.L., La Follette, P.S. (1972). Visual search patterns and experience with radiological images. Radiology, 103(3), 523–528.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(3), 175–181.CrossRefGoogle ScholarPubMed

Latham, G.P., Seijts, G., Crim, D. (2008). The effects of learning goal difficulty level and cognitive ability on performance. Can J Behav Sci/Rev Can Sci Comport, 40(4), 220.Google Scholar

Manning, D.J., Ethell, S.C., Donovan, T. (2004). Detection or decision errors? Missed lung cancer from the posteroanterior chest radiograph. Br J Radiol, 77(915), 231–235.CrossRefGoogle ScholarPubMed

Mazurowski, M.A., Tourassi, G.D. (2011). Exploring the potential of collaborative filtering for user-adaptive mammography education. In: Proceedings of the 2011 Biomedical Sciences and Engineering Conference: Image Informatics and Analytics in Biomedicine. IEEE.Google Scholar

Mazurowski, M.A., Baker, J.A., Barnhart, H.X., Tourassi, G.D. (2010). Individualized computer-aided education in mammography based on user modeling: concept and preliminary experiments. Med Phys, 37(3), 1152–1160.Google Scholar

Mazurowski, M.A., Barnhart, H.X., Baker, J.A., Tourassi, G.D. (2012). Identifying error-making patterns in assessment of mammographic BI-RADS descriptors among radiology residents using statistical pattern recognition. Acad Radiol, 19(7), 865–871.CrossRefGoogle ScholarPubMed

Meng, K., Lipson, J.A. (2011). Utilizing a PACS-integrated ultrasound-guided breast biopsy simulation exercise to reinforce the ACR practice guideline for ultrasound-guided percutaneous breast interventional procedures during radiology residency. Acad Radiol, 18(10), 1324–1328.CrossRefGoogle ScholarPubMed

Rich, E. (1983). Users are individuals: individualizing user models. Int J Man-Machine Stud, 18(3), 199–214.Google Scholar

Samia, H., Khan, S., Lawrence, J., Delaney, C.P. (2013). Simulation and its role in training. Clin Colon Rect Surg, 26(1), 47–55.Google Scholar

Sarwani, N., Tappouni, R., Flemming, D. (2012). Use of a simulation laboratory to train radiology residents in the management of acute radiologic emergencies. AJR. Am J Roentgenol, 199(2), 244–251.Google Scholar

SIMulation, . (2017). Emergent/critical care imaging SIMulation (SIM). Available at: http://widi.xray.ufl.edu/acr-resident-sim/history/ (accessed September 9, 2017).Google Scholar

Su, X., Khoshgoftaar, T.M. (2009). A survey of collaborative filtering techniques. Adv Artif Intell, 2009, 4.CrossRefGoogle Scholar

Towbin, A.J., Paterson, B.E., Chang, P.J. (2008). Computer-based simulator for radiology: an educational tool. Radiographics, 28(1), 309–316.CrossRefGoogle ScholarPubMed

Wang, M., Wang, M., Grimm, L.J., Mazurowski, M.A. (2016a). A computer vision-based algorithm to predict false positive errors in radiology trainees when interpreting digital breast tomosynthesis cases. Exp Syst Applic, 64: 490–499.Google Scholar

Wang, M., Zhang, J., Grimm, L.J., Ghate, S.V. Walsh, R., Johnson, K.S., Lo, J.Y., Mazurowski, M.A. (2016b). Predicting false negative errors in digital breast tomosynthesis among radiology trainees using a computer vision-based approach. Exp Syst Applic, 56, 1–8.Google Scholar

Webb, G.I., Pazzani, M.J., Billsus, D. (2001). Machine learning for user modeling. User Model User-Adapt Interact, 11(1–2), 19–29.CrossRefGoogle Scholar

Zhang, J., Lo, J.Y., Kuzmiak, C.M., Ghate, S.V., Yoon, S.C., Mazurowski, M.A. (2014). Using computer-extracted image features for modeling of error-making patterns in detection of mammographic masses among radiology residents. Med Phys, 41(9), 91907.Google Scholar

Zhang, J., Silber, J.I., Mazurowski, M.A. (2015). Modeling false positive error making patterns in radiology trainees for improved mammography education. J Biomed Inform, 54, 50–57.CrossRefGoogle ScholarPubMed

ACGME. (2011). Task Force on Quality Care and Professionalism. The ACGME 2011 duty hour standards: enhancing quality of care, supervision, and resident professional development. Available at:www.acgme.org/Portals/0/PDFs/jgme-monograph[1].pdf (accessed December 20, 2017).Google Scholar

Ackerman, P.L., Kanfer, R., Shapiro, S.W., Newton, S., Beier, M.E. (2010). Cognitive fatigue during testing: an examination of trait, time-on-task, and strategy influences. Hum Perform, 23, 381–402.CrossRefGoogle Scholar

Ahsberg, E. (2000). Dimensions of fatigue in different workplace populations. Scand J Psychol, 41, 231–241.Google Scholar

Ahsberg, E, Gamberale, F, Gustafsson, K. (2000). Perceived fatigue after mental work: an experimental evaluation of a fatigue inventory. Ergonomics, 43, 252–268.Google Scholar

Akerstedt, T., Knutsson, A., Westerholm, P., Theorell, T., Alfredsson, L., Kecklund, G. (2004). Mental fatigue, work and sleep. J Psychosom Res, 57, 427–433.Google Scholar

Andre, J.T., Owens, D.A. (1999). Predicting optimal accommodative performance from measures of the dark focus of accommodation. Hum Fact, 41, 139–145.CrossRefGoogle ScholarPubMed

Ankrum, D.R. (1996). Viewing distance at computer workstations. Work Place Ergonom, September/October, 10–12.Google Scholar

Backs, R.W., Walrath, L.C. (1992). Eye movement and pupillary response indices of mental workload during visual search of symbolic displays. Appl Ergonom, 23, 243–254.Google Scholar

Barger, L.K., Cade, B.E., Ayas, N.T., Cronin, J.W., Rosner, B., Speizer, F.E., et al. (2005). Extended work shifts and the risk of motor vehicle crashes among interns. N Engl J Med, 352, 125–314.CrossRefGoogle ScholarPubMed

Bellini, L.M., Baime, M., Shea, J.A. (2002). Variation in mood and empathy during internship. JAMA, 287, 3143–3146.CrossRefGoogle ScholarPubMed

Ben-Aroya, Z., Segal, D., Hadar, A., Hallak, M., Friger, M., Katz, M., Mazor, M. (2002). Effect of OB/GYN residents’ fatigue and training level on the accuracy of fetal weight estimation. Fetal Diagn Ther, 17, 177–181.CrossRefGoogle Scholar

Berbaum, K.S., Franken, E.A., Dorfman, D.D., et al. (1990). Satisfaction of search in diagnostic radiology. Invest Radiol, 25, 133–140.Google Scholar

Berbaum, K.S., Dorfman, D.D., Franken, E.A., et al. (2000). Proper ROC analysis and joint ROC analysis of the satisfaction of search effect in chest radiography. Acad Radiol, 7, 945–958.Google Scholar

Berbaum, K.S., Krupinski, E.A., Schartz, K.M., et al. (2015). Satisfaction of search in chest radiography 2015. Acad Radiol, 22, 1457–1465.CrossRefGoogle ScholarPubMed

Berbaum, K.S., Krupinski, E.A., Schartz, K.M., et al. (2016). The influence of a vocalized checklist on detection of multiple abnormalities in chest radiography. Acad Radiol, 23, 413–420.CrossRefGoogle ScholarPubMed

Berlin, L. (2007). Accuracy of diagnostic procedures: has it improved over the past five decades? Am J Roentgenol, 188, 1173–1178.Google Scholar

Bilimoria, K.Y., Chung, J.W., Hedges, L.V., Dahlke, A.R., Love, R., Cohen, M.E., et al. (2016). National cluster-randomized trial of duty-hour flexibility in surgical training. N Engl J Med, 374, 713–727.Google Scholar

Boiselle, P.M., Levine, D., Horwich, P.J., et al. (2008). Repetitive stress symptoms in radiology: prevalence and response to ergonomic interventions. J Am Coll Radiol, 5, 919–923.CrossRefGoogle ScholarPubMed

Boksem, M.A.S., Tops, M. (2008). Mental fatigue: costs and benefits. Brain Res Rev, 59, 125–139.Google Scholar

Boksem, M.A.S., Meijman, T.F., Lorist, M.M. (2006). Mental fatigue, motivation and action monitoring. Biol Psychol, 72, 123–132.CrossRefGoogle ScholarPubMed

Bruno, M.A., Walker, E.A., Abujudeh, H.H. (2015). Understanding and confronting our mistakes: the epidemiology of error in radiology and strategies for error reduction. RadioGraphics, 35, 1668–1676.CrossRefGoogle ScholarPubMed

Bultmann, U., Kant, I., Van den Brandt, P.A., Kasl, S.V. (2002a). Psychosocial work characteristics as risk factors for the onset of fatigue and psychological distress: prospective results from the Maastricht cohort study. Psychol Med, 32, 333–345.Google Scholar

Bultmann, U., Kant, I., Kasi, S.V., Schroer, K.A.P., Swaen, G.M.H., van den Brandt, P.A. (2002b). Lifestyle factors as risk factors for fatigue and psychological distress in the working population: prospective results from the Maastricht cohort study. J Occup Environ Med, 44, 116–124.Google Scholar

Burnside, E.S., Park, J.M., Fine, J.P., Sisney, G.A. (2005). The use of batch reading to improve the performance of screening mammography. Am J Roentgenol, 185, 790–796.Google Scholar

Caldwell, J.A., Caldwell, J.L. (2016). Fatigue in Aviation: A Guide to Staying Awake at the Stick. New York, NY: Routledge.Google Scholar

Chi, C.F., Lin, F.T. (1998). A comparison of seven visual fatigue assessment techniques in three data-acquisition VDT tasks. Hum Fact, 40, 577–590.Google Scholar

Cornell Musculoskeletal Discomfort Questionnaire for Sedentary Workers. Cornell University Ergonomics Web. Available at: http://ergo.human.cornell.edu/ahmsquest.html (accessed April 17, 2017).Google Scholar

de Mello, M.T., Narciso, F.V., Tufik, S., Paiva, T., Spence, D.W., BaHammam, A.S., et al. (2013). Sleep disorders as a cause of motor vehicle collisions. Int J Prevent Med, 4, 246–257.Google Scholar

Department of Health. (2010). European Working Time Directive. Available at: http://webarchive.nationalarchives.gov.uk/ andwww.dh.gov.uk/en/Managingyourorganisation/Workforce/Workforceplanninganddevelopment/Europeanworkingtimedirective/index.htm (accessed December 20, 2017).Google Scholar

Dillon, T.W., Emurian, H.H. (1996). Some factors affecting reports of visual fatigue resulting from use of a VDU. Comput Hum Behav, 12, 49–59.Google Scholar

Dinnes, J., Moss, S., Melia, J., Blanks, R., Song, F., Kleijnen, J. (2001). Effectiveness and cost-effectiveness of double reading of mammograms in breast cancer screening: findings of a systematic review. Breast. 10(6), 455–463.CrossRefGoogle ScholarPubMed

Dorrian, J., Hussey, F., Dawson, D. (2007). Train driving efficiency and safety: examining the cost of fatigue. J Sleep Res, 16, 1–11.Google Scholar

Dreyer, K.J., Geis, J.R. (2017). When machines think: radiology’s next frontier. Radiology, 285, 713–718.CrossRefGoogle ScholarPubMed

Duffy, V.G., Chan, A.H.S. (2002). Effects of virtual lighting on visual performance and eye fatigue. Hum Fact Ergonom Manufact, 12, 193–209.CrossRefGoogle Scholar

Ebenholtz, S.M. (2001). Oculomotor Systems and Perception. New York, NY: Cambridge University Press.CrossRefGoogle Scholar

European Cockpit Association. (2012). Barometer on pilt fatigue. Available at: www.eurocockpit.be/positions-publications/barometer-pilot-fatigue (accessed December 20, 2017).Google Scholar

Fuchs, A.F., Binder, M.D. (1983). Fatigue resistance of human extraocular muscles. J Neurophysiol, 49, 28–34.CrossRefGoogle ScholarPubMed

Gale, A.G., Murray, D., Millar, K., Worthington, B.S. (1984). Circadian variation in radiology. Adv Psychol, 22, 313–321.Google Scholar

Gates, D.H., Dingwell, J.B. (2008). The effects of neuromuscular fatigue on task performance during repetitive goal-directed movements. Exp Brain Res, 187, 573–585.CrossRefGoogle Scholar

Grantcharov, T.P., Bardram, L., Funch-Jensen, P., Rosenberg, J. (2001). Laparoscopic performance after one night on call in a surgical department: prospective study. Br Med J, 323, 1222–1223.Google Scholar

Gur, D., Bandos, A.I., Cohen, C.S., Hakim, C.M., Hardesty, L.A., Ganott, M.A., et al. (2008). The “laboratory” effect: comparing radiologists’ performance and variability during prospective clinical and laboratory mammography interpretations. Radiology, 249, 47–53.Google Scholar

Hancock, P.A. (2013). In search of vigilance: the problem of iatrogenically created psychological phenomena. Am Psychol, 68, 97–109.CrossRefGoogle ScholarPubMed

Hanna, T.N., Lamoureux, C., Krupinski, E.A., Weber, S., Johnson, J.O. (2018a). Effect of shift schedule, and volume on interpretative accuracy: a retrospective analysis of 2.9 million radiologic examinations. Radiology, 287, 205–212.Google Scholar

Hanna, T., Zygmont, M., Peterson, R., Shekhani, H., Theriot, D., Johnson, J.O., Krupinski, E.A. (2018b). The effects of fatigue from overnight shifts on radiology search patterns and diagnostic performance. J Am Coll Radiol, pii: S1546-1440(17)31661-7.Google ScholarPubMed

Hardy, G.E., Shapiro, D.A., Borrill, C.S. (1997). Fatigue in the workforce of National Health Service trusts: levels of symptomatology and links with minor psychiatric disorder, demographic, occupational and work role factors. J Psychosom Res, 43, 83–92.CrossRefGoogle ScholarPubMed

Harris, J.D., Staheli, G., LeClere, L., Andersone, D., McCormick, F. (2015). What effects have resident work-hour changes had on education, quality of life, and safety? A systematic review. Clin Orthop Rel Res, 473, 1600–1608.Google Scholar

Hasebe, S., Graf, E.W., Schor, C. (2001). Fatigue reduces tonic accommodation. Ophthalmic Physiol Opt, 21, 151–160.CrossRefGoogle ScholarPubMed

Heron, G., Charman, W.N., Gray, L.S. (1999). Accommodation responses and ageing. Invest Ophthalmol Visual Sci, 40, 2872–2883.Google Scholar

Ho, J.C., Lee, M.B., Chen, R.Y., Chen, C.J., Chang, W.P., Yeh, C.Y., et al. (2013). Work-related fatigue among medical personnel in Taiwan. J Formos Med Assoc, 112, 608–615.CrossRefGoogle ScholarPubMed

Hoffmann, J.C., Mittal, S., Hoffmann, C.H., Fadl, A., Baadh, A., Katz, D.S., Flug, J. (2016). Combating the health risks of sedentary behavior in the contemporary radiology reading room. Am J Roentgenol, 206, 1135–1140.CrossRefGoogle ScholarPubMed

Horowitz, T.S., Cade, B.E., Wolfe, J.M., Czeisler, C.A. (2003). Searching night and day: a dissociation of effects of circadian phase and time awake on visual selective attention and vigilance. Psychol Sci, 14, 549–557.Google Scholar

Howard, S.K., Gaba, D.M., Smith, B.E., Weinger, M.B., Herndon, C., Keshavacharya, S., Rosekind, M.R. (2003). Simulation of rested versus sleep-deprived anesthesiologists. Anesthesiology, 98, 1345–1355.Google Scholar

Jaschinski-Kruza, W. (1988). Visual strain during VDU work: the effect of viewing distance and dark focus. Ergonomics, 31, 1449–1465.CrossRefGoogle ScholarPubMed

Kahn, C.E. (2017). From images to actions: opportunities for artificial intelligence in radiology. Radiology, 285, 719–720.CrossRefGoogle ScholarPubMed

Khan, F.A., Bhalla, S., Jost, G. (2002). Results of the 2001 survey of the American Association of Academic chief residents in radiology. Acad Radiol, 9, 89–97.CrossRefGoogle Scholar

Kohli, M., Prevedello, L.M., Filice, R.W., Geis, J.R. (2017). Implementing machine learning in radiology practice and research. Am J Roentgenol, 208, 754–760.Google Scholar

Komiushina, T.A. (2000). Physiological mechanisms of the etiology of visual fatigue during work involving visual stress. Vestnik Oftalmologii, 116, 33–36.Google Scholar

Krupinski, E.A., Berbaum, K.S. (2009). Measurement of visual strain in radiologists. Acad Radiol, 16, 947–950.Google Scholar

Krupinski, E., Reiner, B.I. (2012). Real-time occupational stress and fatigue measurement in medical imaging practice. J Digit Imag, 25, 319–324.Google Scholar

Krupinski, E.A., Berbaum, K.S., Caldwell, R.T., Schartz, K.M., Kim, J. (2010). Long radiology workdays reduce detection and accommodation accuracy. J Am Coll Radiol, 7, 698–704.CrossRefGoogle ScholarPubMed

Krupinski, E.A., Berbaum, K.S., Caldwell, R.T., Schartz, K.M., Madsen, M.T., Kramer, D.J. (2012). Do long radiology workdays affect nodule detection in dynamic CT interpretation? J Am Coll Radiol, 9, 191–198.CrossRefGoogle Scholar

Krupinski, E.A., Berbaum, K.S., Schartz, K.M., Caldwell, R.T., Madsen, M.T. (2017a). The impact of fatigue on satisfaction of search in chest radiography. Acad Radiol, 24, 1058–1063.Google Scholar

Krupinski, E.A., Schartz, K.M., van Tassell, M.S., Madsen, M.T., Caldwell, R.T., Berbaum, K.S. (2017b). Effect of fatigue on reading computed tomography examination of the multiple injured patient. J Med Imag, 4, 035504.CrossRefGoogle Scholar

Landrigan, C.P., Rothschild, J.M., Cronin, J.W., Kaushal, R., Burdick, E., Katz, J.T., et al. (2004). Effect of reducing interns’ work hours on serious medical errors in intensive care units. N Engl J Med, 351, 1838–1848.Google Scholar

Lavine, R.A., Sibert, J.L., Gokturk, M., Dickens, B. (2002). Eye-tracking measures and human performance in a vigilance task. Aviat Space Environ Med, 73, 367–372.Google Scholar

Lee, J.G., Jun, S., Cho, Y.W., Lee, H., et al. (2017). Deep learning in medical imaging: general overview. Korean J Radiol, 18, 570–584.CrossRefGoogle ScholarPubMed

Levine, A.C., Adusumilli, J., Landrigan, C.P. (2010). Effects of reducing or eliminating resident work shifts over 16 hours: a systematic review. Sleep, 33, 1043–1053.CrossRefGoogle ScholarPubMed

Lockley, S.W., Barger, L.K., Ayas, N.T., Rothschild, J.M., Czeisler, C.A., Landrigan, C.P. (2007). Effects of health care provider work hours and sleep deprivation on safety and performance. Jt Comm J Qual Patient Saf, 33(11 Suppl), 7–18.Google ScholarPubMed

Lorist, M.M., Kernell, D., Meijman, T.F., Zijdewind, I. (2002). Motor fatigue and cognitive task performance in humans. J Physiol, 545, 313–319.Google Scholar

Mann, F.A., Danz, P.L. (1993). The night stalker effect: quality improvements with a dedicated night-call rotation. Invest Radiol, 28, 92–96.CrossRefGoogle ScholarPubMed

Megaw, E.D. (1995). The definition and measurement of visual fatigue. In: Wilson, J.R., Corlett, E.N. (eds.) Evaluation of Human Work: a Practical Ergonomics Methodology. Philadelphia, PA: Taylor & Francis. pp. 840–863.Google Scholar

Mehta, R.K., Agnew, M.J. (2012). Influence of mental workload on muscle endurance, fatigue, and recovery during intermittent static work. Eur J Appl Physiol, 112, 2891–2902.Google Scholar

Mockel, T., Beste, C., Wascher, E. (2015). The effects of time on task in response selection – an ERP study of mental fatigue. Sci Rep, 5, 10113.CrossRefGoogle ScholarPubMed

Moonesinghe, S.R., Lowery, J., Shahi, N., Millen, A., Beard, J.D. (2011). Impact of reduction in working hours for doctors in training on postgraduate medical education and patients’ outcomes: systematic review. Br Med J, 342, d1580.Google Scholar

Murata, A., Uetake, A., Otsuka, M., Takasaw, Y. (2001). Proposal of an index to evaluate visual fatigue induced during visual display terminal tasks. Int J Hum-Comput Interact, 13, 305–321.Google Scholar

Mutti, D.O., Zadnik, K. (1996). Is computer use a risk factor for myopia? J Am Optom Assn, 67, 521–530.Google ScholarPubMed

Owens, J.A. (2001). Sleep loss and fatigue in medical training. Curr Opin Pulm Med, 7, 411–418.CrossRefGoogle ScholarPubMed

Patterson, P.D., Suffoletto, B.P., Kupas, D.F., Weaver, M.D., Hostler, D. (2010). Sleep quality and fatigue among prehospital providers. Prehosp Emerg Care, 14, 187–193.CrossRefGoogle ScholarPubMed

Patterson, P.D., Weaver, M.D., Frank, R.C., Warner, C.W., Martin-Gill, C., Guyette, F.X., et al. (2012). Association between poor sleep, fatigue, and safety outcomes in emergency medical services providers. Prehosp Emerg Care, 6, 86–97.Google Scholar

Pigeon, W.R., Sateia, M.J., Ferguson, R.J. (2003). Distinguishing between excessive daytime sleepiness and fatigue – toward improved detection and treatment. J Psychosom Res, 54, 61–69.Google Scholar

Pronovost, P., Needham, D., Berenholtz, S., Sinopoli, D., Chu, H., Cosgrove, S., et al. (2006). An intervention to decrease catheter-related bloodstream infections in the ICU. N Engl J Med, 355, 2725–2732.Google Scholar

Reuss, L., O’Connor, S.C., Cho, K.H., et al. (2003). Carpal tunnel syndrome and cubital tunnel syndrome: work-related musculoskeletal disorders in four symptomatic radiologists. Am J Roentgenol, 181, 37–42.Google Scholar

Rodrigues, J.C., Morgan, S., Augustine, K., et al. (2014). Musculoskeletal symptoms amongst clinical radiologists and the implications of reporting environment ergonomics- a multicentre questionnaire study. J Digit Imag, 27, 255–261.CrossRefGoogle ScholarPubMed

Rogers, A.E. (2008). The effects of fatigue and sleepiness on nurse performance and patient safety. In: Hughes, R.G. (ed.). Patient Safety and Quality: An Evidence-Based Handbook for Nurses. Rockville, MD: Agency for Healthcare Research and Quality.Google Scholar

Rogers, A.E., Hwang, W.T., Scott, L.D., Aiken, L.H., Dinges, D.F. (2004). The working hours of hospital staff nurses and patient safety. Health Aff (Millwood), 23, 202–212.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

Rosen, I.M., Shea, J.A., Bellini, L.M. (2003). Residents’ work hours. N Engl J Med, 348, 664–666.Google ScholarPubMed

Rozenshtein, A., Bauman-Fishkin, O., Fishkin, I., Homel, P. (2003). Radiology residency call in the Northeastern United States: comparison of difficulty and frequency in programs of different sizes. Acad Radiol, 10, 559–564.Google Scholar

Rutter, C.M., Taplin, S. (2000). Assessing mammographers’ accuracy. A comparison of clinical and test performance. J Clin Epidemiol, 53, 443–450.Google Scholar

Ruutiainen, A.T., Durand, D.J., Scanlon, M.H., Itri, J.N. (2013). Increased error rates in preliminary reports issued by radiology residents working more than 10 consecutive hours overnight. Acad Radiol, 20, 305–311.Google Scholar

Sanchez-Roman, F.R., Perez-Lucio, C., Juarez-Ruiz, C., Velez-Zamora, N.M., Jimenez-Villarruel, M. (1996). Risk factors for asthenopia among computer terminal operators. Salud Publ Mex, 38, 189–196.Google Scholar

Scott, J.N., Romano, C.C. (2003). On-call services provided by radiology residents in a university hospital environment. Can Assn Radiol J, 54, 104–108.Google Scholar

Scott, H., Evan, A., Gale, A., Murphy, A., Reed, J. (2009). The relationship between real life breast screening and an annual self-assessment scheme. Proc SPIE Med Imag, 7263, 72631E-1–72631E-7.Google Scholar

Seidel, R.L., Krupinski, E.A. (2017). The agony of it all: musculoskeletal discomfort in the reading room. J Am Coll Radiol, 14, 1620–1625.Google Scholar

Siegel, E.L., Reiner, B. (2002). Image workflow. In: Dreyer, K.J., Mehta, A., Thrall, J.H. (eds.) PACS: A Guide to the Digital Revolution. New York, NY: Springer-Verlag, pp. 161–190.CrossRefGoogle Scholar

Sirevaag, E.J., Stern, J.A. (2000). Ocular measures of fatigue and cognitive factors. In: Backs, R.W., Boucsein, W. (eds.) Engineering Psychophysiology: Issues and Applications. Maywah, NJ: Lawrence Erlbaum, pp. 269–287.Google Scholar

Sommerich, C.M., Joines, S.M.B., Psihogios, J.P. (2001). Effects of computer monitor viewing angle and related factors on strain, performance, and preference outcomes. Hum Fact, 43, 39–55.CrossRefGoogle ScholarPubMed

Stern, J.A., Boyer, D., Schroeder, D., Touchstone, M. (1994). Blinks, saccades, and fixation pauses during vigilance task performance. I. Time on task. FAA Off Aviat Med Rep, FAA-AM-94- 26, 1–44.Google Scholar

Stinton, C., Jenkinson, D., Adekanmbi, V., Clarke, A., Taylor-Phillips, S. (2017). Does time of day influence cancer detection and recall rates in mammography? Proc SPIE Med Imag, 10136, 10136B.Google Scholar

Stone, M.D., Doyle, J., Bosch, R.J., Bothe, A., Steele, G. (2000). Effect of resident call system on ABSITE performance. Surgery, 28, 465–471.Google Scholar

Takahashi, K., Sasaki, T., Hosokawa, T., Kurasaki, M., Saito, K. (2001). Combined effects of working environmental conditions in VDT work. Ergonomics, 44, 562–570.Google Scholar

Taylor, P., Potts, H.W.W. (2008). Computer aids and human second reading as interventions in screening mammography: two systematic reviews to compare effects on cancer detection and recall rate. Eur J Cancer, 44, 798–807.Google Scholar

Taylor-Phillips, S., Clarke, A., Wallis, M., Wheaton, M, Duncan, A, Gale, A.G. (2001). The time course of cancer detection performance. Proc SPIE Med Imag, 7966, 796605-1–796605-8.Google Scholar

Taylor-Phillips, S., Wallis, M.G., Jenkinson, D., Adekanmbi, V., Parsons, H., Dunn, J., et al. (2016). Effect of using the same vs different order for second readings of screening mammograms on rates of breast cancer detection: a randomized clinical trial. JAMA, 315, 1956–1965.Google Scholar

Thompson, A.C., Kremer Prill, M.J., Biswal, S., et al. (2014). Factors associated with repetitive strain, and strategies to reduce injury among breast-imaging radiologists. J Am Coll Radiol, 11, 1074–1079.CrossRefGoogle ScholarPubMed

Townsend, R.R., Manco-Johnson, M.L. (1995). Night call in US radiology residency programs. Acad Radiol, 2, 810–815.CrossRefGoogle ScholarPubMed

Trinkoff, A.M., Le, R., Geiger-Brown, J., Lipscomb, J. (2007). Work schedule, needle use, and needlestick injuries among registered nurses. Infect Control Hosp Epidemiol, 28, 156–164.Google Scholar

Turville, K.L., Psihogios, J.P., Ulmer, T.R., Mirka, G.A. (1998). The effects of video display terminal height on the operator: a comparison of the 15” and 40” recommendation. Appl Ergonom, 9, 239–246.CrossRefGoogle Scholar

Tyrrell, R.A., Leibowitz, H.W. (1990). The relation of vergence effort to reports of visual fatigue following prolonged near work. Hum Fact, 32, 341–357.Google Scholar

Van Cutsem, J., Marcora, S., De Pauw, K., Bailey, S., Meeusen, R., Roelands, B. (2017). The effects of mental fatigue on physical performance: a systematic review. Sports Med, 47, 1569–1588.CrossRefGoogle ScholarPubMed

Van Orden, K.F., Jung, T.P., Makeig, S. (2000). Combined eye activity measures accurately estimate changes in sustained visual task performance. Biol Psychol, 52, 221–240.Google Scholar

Veasey, S., Rosen, R., Barzansky, B., Rosen, I., Owens, J. (2002). Sleep loss and fatigue in residency training: a reappraisal. JAMA, 288, 1116–1124.CrossRefGoogle ScholarPubMed

Waite, S., Kolla, S., Jeudy, J., Legasto, A., Macknik, S.L., Martinez-Condo, S., Krupinski, E.A., Reede, D.L. (2017). Tired in the reading room: the influence of fatigue in radiology. J Am Coll Radiol, 14, 191–197.CrossRefGoogle ScholarPubMed

Wascher, E., Getzmann, S. (2014). Rapid mental fatigue amplifies age-related attentional deficits. J Psychophys, 28, 215–224.Google Scholar

Watanabe, Y. (2007). Preface and mini-review: fatigue science for human health. In: Watanabe, Y., Evengård, B., Natelson, B., Jason, L., Kuratsune, H. (eds.) Fatigue Science for Human Health. New York, NY: Springer, pp. 5–11.Google Scholar

Watten, R.G., Lie, I. (1992). Time factors in VDT-induced myopia and visual fatigue: an experimental study. J Hum Ergol, 21, 13–20.Google Scholar

Watten, R.G., Lie, I., Birketvedt, O. (1994). The influence of long-term visual near-work on accommodation and vergence: a field study. J Hum Ergol, 23, 27–39.Google ScholarPubMed

Whetsell, J.F. (2003). Changing the law, challenging the culture: rethinking the “sleepy resident” problem. Ann Health Law, 12, 23–73.Google Scholar

Wolska, A., Switula, M. (1999). Luminance of the surround and visual fatigue of VDT operators. Int J Occup Saf Ergonom, 5, 553–581.Google Scholar

Yunfang, L., Wenjing, W., Bingshuang, H., Changji, L., Chenglie, Z. (2000). Visual strain and working capacity in computer operators. Homeostasis Health Dis, 40, 27–29.Google Scholar

Ziefle, M. (1998). Effects of display resolution on visual performance. Hum Fact, 40, 554–568.Google Scholar

Badano, A., Revie, C., Casertano, A., Cheng, W.C., Green, P., Kimpe, T. et al. (2015). Consistency and standardization of color in medical imaging: a consensus report. J Digit Imag, 28, 41–52.CrossRefGoogle ScholarPubMed

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 results. Telemed J eHealth, 23, 155–191.Google Scholar

Bautista, P.A., Hashimoto, N., Yagi, Y. (2014). Color standardization in whole slide imaging using a color calibration slide. J Pathol Inform, 5, 4.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-century health care. J Am Coll Radiol, 3, 409–412.Google Scholar

Bhargava, R., Madabhushi, A. (2016). Emerging themes in image informatics and molecular analysis for digital pathology. Annu Rev Biomed Eng, 18, 387–412.Google Scholar

Brunye, T.T., Carney, P.A., Allison, K.H., Shapiro, L.G., Weaver, D.L., Elmore, J.G. (2014). Eye movements as an index of pathologist visual expertise: a pilot study. PLoS One, 9, e103447.Google Scholar