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12 - The First Moments of Medical Image Perception

from Part II - Science of Image Perception

Published online by Cambridge University Press:  20 December 2018

By
Jeremy M. Wolfe ,
Karla K. Evans  and
Trafton Drew
Edited by
Ehsan Samei  and
Elizabeth A. Krupinski
Ehsan Samei
Affiliation:
Duke University Medical Center, Durham
Elizabeth A. Krupinski
Affiliation:
Emory University, Atlanta
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The Handbook of Medical Image Perception and Techniques , pp. 188 - 196
Publisher: Cambridge University Press
Print publication year: 2018

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References

Alvarez, G.A. (2011). Representing multiple objects as an ensemble enhances visual cognition. Trends Cogn Sci, 15(3), 122–131.Google Scholar
Ariely, D. (2001). Seeing sets: representation by statistical properties. Psychol Sci, 12(2), 157–162.Google Scholar
Bertram, R., Helle, L., Kaakinen, J.K., Svedstrom, E. (2013). The effect of expertise on eye movement behaviour in medical image perception. PLoS One, 8(6), e66169.CrossRefGoogle ScholarPubMed
Biederman, I. (1972). Perceiving real-world scenes. Science, 177(43), 77–80.CrossRefGoogle ScholarPubMed
Biederman, I., Glass, A.L., Stacy, E.W. (1973). Searching for objects in real-world scenes. J Exp Psychol Gen, 97, 22–27.Google Scholar
Biederman, I., Mezzanotte, R.J., Rabinowitz, J.C. (1982). Scene perception: detecting and judging objects undergoing relational violations. Cogn Psychol, 14, 143–177.Google Scholar
Brady, T.F., Shafer-Skelton, A., Alvarez, G.A. (2017). Global ensemble texture representations are critical to rapid scene perception. J Exp Psychol: Hum Percept Perform, 43(6), 1160–1176.Google ScholarPubMed
Carmody, D.P., Nodine, C.F., Kundel, H.L. (1981). Finding lung nodules with and without comparative visual scanning. Percept Psychophys, 29(6), 594–598.CrossRefGoogle ScholarPubMed
Castelhano, M.S., Henderson, J.M. (2007). Initial scene representations facilitate eye movement guidance in visual search. J Exp Psychol: Hum Percept Perform, 33(4), 753–763.Google Scholar
Chong, S.C., Treisman, A. (2003). Representation of statistical properties. Vision Res, 43(4), 393–404.Google Scholar
Crick, F. (1984). Function of the thalamic reticular complex: the searchlight hypothesis. Proc Natl Acad Sci USA, 81, 4586–4590.CrossRefGoogle ScholarPubMed
Crick, F., Koch, C. (1990). Towards a neurobiological theory of consciousness. Semin Neurosci, 2, 263–275.Google Scholar
Drew, T., Evans, K., Vo, M.L.-H., Jacobson, F.L., Wolfe, J.M. (2013). Informatics in radiology: what can you see in a single glance and how might this guide visual search in medical images? Radiographics, 33, 263–274.CrossRefGoogle Scholar
Drewes, J., Trommershauser, J., Gegenfurtner, K.R. (2011). Parallel visual search and rapid animal detection in natural scenes. J Vision, 11(2), 20.CrossRefGoogle ScholarPubMed
Ebner, L., Tall, M., Roychoudhury, K., Ly, D.L., Roos, J.E., Napel, S., et al. (2016). Variations in the functional visual field for detection of lung nodules on chest computed tomography: impact of nodule size, distance, and local lung complexity. Med Phys, 44, 3483–3490.CrossRefGoogle Scholar
Egeth, H.E., Virzi, R.A., Garbart, H. (1984). Searching for conjunctively defined targets. J Exp Psychol: Hum Percept Perform, 10, 32–39.Google ScholarPubMed
Ehinger, K.A., Hidalgo-Sotelo, B., Torralba, A., Oliva, A. (2009). Modeling search for people in 900 scenes: a combined source model of eye guidance. Vis Cogn, 17(6), 945–978.CrossRefGoogle ScholarPubMed
Evans, K.K., Treisman, A. (2005). Perception of objects in natural scenes: is it really attention free? J Exp Psychol: Hum Percept Perform, 31(6), 1476–1492.Google Scholar
Evans, K.K., Georgian-Smith, D., Tambouret, R., Birdwell, R.L., Wolfe, J.M. (2013). The gist of the abnormal: above-chance medical decision making in the blink of an eye. Psychon Bull Rev, 20(6), 1170–1175.Google Scholar
Evans, K., Haygood, T.M., Cooper, J., Culpan, A.M., Wolfe, J.M. (2016). A half-second glimpse often lets radiologists identify breast cancer cases even when viewing the mammogram of the opposite breast Proc Natl Acad Sci USA, 113(37), 10292–10297.Google Scholar
Fei-Fei, L., Iyer, A., Koch, C., Perona, P. (2007). What do we perceive in a glance of a real-world scene? J Vision, 7(1), 10.Google Scholar
Freedman, D.J., Riesenhuber, M., Poggio, T., Miller, E.K. (2002). Visual categorization and the primate prefrontal cortex: neurophysiology and behavior. J Neurophysiol, 88(2), 929–941.Google Scholar
Gierach, G.L., Li, H., Loud, J.T., Greene, M.H., Chow, C.K., Lan, L., et al. (2014). Relationships between computer-extracted mammographic texture pattern features and BRCA1/2 mutation status: a cross-sectional study. Breast Cancer Res, 16(4), 424.Google ScholarPubMed
Greene, M.R., Oliva, A. (2008). Recognition of natural scenes from global properties: seeing the forest without representing the trees. Cogn Psychol, 58(2), 137–176.CrossRefGoogle ScholarPubMed
Greene, M.R., Oliva, A. (2009). The briefest of glances: the time course of natural scene understanding. Psychol Sci, 20(4), 464–472.Google Scholar
Grindley, G.C., Townsend, V. (1968). Voluntary attention in peripheral vision and its effects on acuity and differential thresholds. Q J Exp Psychol, 20(1), 11–19.Google Scholar
Helmholtz, H. v. (1924). Treatise on Physiological Optics (Southall, trans. from 3rd German ed. of 1909, ed.). Rochester, NY: Optical Society of America.Google Scholar
Henderson, J.M., Ferreira, F. (2004). Scene perception for psycholinguists. In: Henderson, J.M., Ferreira, F. (eds.) The Interface of Language, Vision, and Action: Eye Movements and the Visual World. New York, NY: Psychology Press, pp. 1–58.Google Scholar
Kallenberg, M., Petersen, K., Nielsen, M., Ng, A.Y., Pengfei, D., Igel, C., et al. (2016). Unsupervised deep learning applied to breast density segmentation and mammographic risk scoring. IEEE Trans Med Imag, 35(5), 1322–1331.Google Scholar
Koehler, K., Eckstein, M.P. (2017). Beyond scene gist: objects guide search more than scene background. J Exp Psychol: Hum Percept Perform, 43(6), 1177–1193.Google ScholarPubMed
Krupinski, E.A. (1996). Visual scanning patterns of radiologists searching mammograms. Acad Radiol, 3(2), 137–144.CrossRefGoogle ScholarPubMed
Kundel, H.L. (2007). How to minimize perceptual error and maximize expertise in medical imaging. Proc SPIE Med Imag, 6515, 651508.CrossRefGoogle Scholar
Kundel, H.L., La Follette, P.S., Jr. (1972). Visual search patterns and experience with radiological images. Radiology, 103(3), 523–528.CrossRefGoogle ScholarPubMed
Kundel, H.L., Nodine, C.F. (1975). Interpreting chest radiographs without visual search. Radiology, 116, 527–532.Google Scholar
Kundel, H.L., Nodine, C.F. (2004). Modeling visual search during mammogram viewing. Proc SPIE Med Imag, 5372, 538063.Google Scholar
Kundel, H.L., Nodine, C.F., Krupinski, E.A., Mello-Thoms, C. (2008). Using gaze-tracking data and mixture distribution analysis to support a holistic model for the detection of cancers on mammograms. Acad Radiol, 15(7), 881–886.CrossRefGoogle ScholarPubMed
Li, F.F., VanRullen, R., Koch, C., Perona, P. (2002). Rapid natural scene categorization in the near absence of attention. Proc Natl Acad Sci USA, 99(14), 9596–9601.Google Scholar
Li, H., Giger, M.L., Lan, L., Janardanan, J., Sennett, C.A. (2014). Comparative analysis of image-based phenotypes of mammographic density and parenchymal patterns in distinguishing between BRCA1/2 cases, unilateral cancer cases, and controls. J Med Imag, 1(3), 031009.CrossRefGoogle ScholarPubMed
Maljkovic, V., Nakayama, K. (1994). Priming of popout: I. Role of features. Mem Cognit, 22(6), 657–672.CrossRefGoogle ScholarPubMed
Navon, D. (1977). Forest before the trees: the precedence of global features in visual perception. Cogn Psychol, 9, 353–383.Google Scholar
Neisser, U. (1967). Cognitive Psychology. New York, NY: Appleton-Century-Crofts.Google Scholar
Nielsen, M., Vachon, C.M., Scott, C.G., Chernoff, K., Karemore, G., Karssemeijer, N., et al. (2014). Mammographic texture resemblance generalizes as an independent risk factor for breast cancer. Breast Cancer Res, 16(2), R37.Google Scholar
Nodine, C.F., Kundel, H.L., Lauver, S.C., Toto, L.C. (1996). Nature of expertise in searching mammograms for breast masses. Acad Radiol, 3(12), 1000–1006.Google Scholar
Nodine, C.F., Mello-Thoms, C., Kundel, H.L., Weinstein, S.P. (2002). Time course of perception and decision making during mammographic interpretation. AJR Am J Roentgenol, 179(4), 917–923.CrossRefGoogle ScholarPubMed
Nordfang, M., Wolfe, J.M. (2014). Guided search for triple conjunctions. Atten Percept Psychophys, 76(6), 1535–1559.CrossRefGoogle ScholarPubMed
Oliva, A. (2005). Gist of the scene. In: Itti, L., Rees, G., Tsotsos, J. (eds.) Neurobiology of Attention. San Diego, CA: Academic Press / Elsevier, pp. 251–257.Google Scholar
Oliva, A., Schyns, P.G. (1997). Coarse blobs or fine edges? Evidence that information diagnosticity changes the perception of complex visual stimuli. Cogn Psychol, 34(1), 72–107.CrossRefGoogle ScholarPubMed
Oliva, A., Torralba, A. (2001). Modeling the shape of the scene: a holistic representation of the spatial envelope. Int J Comput Vis, 42(3), 145–175.CrossRefGoogle Scholar
Oliva, A., Torralba, A. (2006). Building the gist of a scene: the role of global image features in recognition. Prog Brain Res, 155, 23–36.CrossRefGoogle ScholarPubMed
O’Regan, K. (1992). Solving the “real” mysteries of visual perception. The world as an outside memory. Can J Psychol, 46, 461–488.Google Scholar
Posner, M.I. (1980). Orienting of attention. Q J Exp Psychol, 32, 3–25.Google Scholar
Potter, M.C., Faulconer, B.A. (1975). Time to understand pictures and words. Nature, 253, 437–438.CrossRefGoogle ScholarPubMed
Roskies, A. (1999). The binding problem. Neuron, 24(1), 7–9.CrossRefGoogle ScholarPubMed
Ross, M.G., Oliva, A. (2010). Estimating perception of scene layout properties from global image features. J Vision, 10(1), 1–25.Google Scholar
Sanders, A.F., Houtmans, M.J.M. (1985). Perceptual modes in the functional visual field. Acta Psychol, 58, 251–261.Google Scholar
Sanocki, T., Epstein, W. (1997). Priming spatial layout of scenes. Psychol Sci, 8, 374–378.CrossRefGoogle Scholar
Schill, H., Culpan, A.-M., Wolfe, J.M., Evans, K.K. (2017). Detecting the “gist” of breast cancer in mammograms three years before the cancer appears. Paper presented at the Annual Meeting of the Vision Science Society.CrossRefGoogle Scholar
Scutt, D., Lancaster, G.A., Manning, J.T. (2006). Breast asymmetry and predisposition to breast cancer. Breast Cancer Res, 8(2), R14.CrossRefGoogle ScholarPubMed
Sigala, N., Logothetis, N.K. (2002). Visual categorization shapes feature selectivity in the primate temporal cortex. Nature, 415(6869), 318–320.Google Scholar
Swensson, R.G. (1980). A two-stage detection model applied to skilled visual search by radiologists. Percept Psychophys, 27(1), 11–16.Google Scholar
Thorpe, S.J., Gegenfurtner, K.R., Fabre-Thorpe, M., Bulthoff, H.H. (2001). Detection of animals in natural images using far peripheral vision. Eur J Neurosci, 14(5), 869–876.CrossRefGoogle ScholarPubMed
Treisman, A. (1985). Preattentive processing in vision. Comput Vision, Graphics Image Proc, 31, 156–177.Google Scholar
Treisman, A. (1996). The binding problem. Curr Opin Neurobiol, 6, 171–178.CrossRefGoogle ScholarPubMed
Treisman, A. (1998). Feature binding, attention and object perception. Phil Trans R Soc Lond B Biol Sci, 353(1373), 1295–1306.Google Scholar
Treisman, A., Gelade, G. (1980). A feature-integration theory of attention. Cogn Psychol, 12, 97–136.CrossRefGoogle ScholarPubMed
Tversky, A., Kahneman, D. (1983). Extensional versus intuitive reasoning: the conjunction fallacy in probability judgment. Psychol Rev, 90(4), 293–315.Google Scholar
Vo, M.L.-H., Wolfe, J.M. (2015). The role of memory for visual search in scenes. Ann NY Acad Sci, 1339, 72–81.Google Scholar
von der Malsburg, C. (1981). The correlation theory of brain function. In: Domany, E., van Hemmen, J.L., Schulten, K. (eds.) Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany, Internal Report 81–2. Reprinted in Models of Neural Networks II (1994). Berlin, Germany: Springer.Google Scholar
Wagemans, J. (1997). Characteristics and models of human symmetry detection. Trends Cogn Sci, 1(9), 346–352.Google Scholar
Wang, J., Shidfar, A., Ivancic, D., Ranjan, M., Liu, L., Choi, M.R., et al. (2017). Overexpression of lipid metabolism genes and PBX1 in the contralateral breasts of women with estrogen receptor-negative breast cancer. Int J Cancer, 140(11), 2484–2497.Google Scholar
Wolfe, J.M. (1994). Guided search 2.0: a revised model of visual search. Psychon Bull Rev, 1(2), 202–238.CrossRefGoogle ScholarPubMed
Wolfe, J.M. (2003). Moving towards solutions to some enduring controversies in visual search. Trends Cogn Sci, 7(2), 70–76.Google Scholar
Wolfe, J.M. (2007). Guided search 4.0: current progress with a model of visual search. In: Gray, W. (ed.) Integrated Models of Cognitive Systems. New York, NY: Oxford Press, pp. 99–119.Google Scholar
Wolfe, J.M., Bennett, S.C. (1997). Preattentive object files: shapeless bundles of basic features. Vision Res, 37(1), 25–43.CrossRefGoogle ScholarPubMed
Wolfe, J.M., Cave, K.R. (1999). The psychophysical evidence for a binding problem in human vision. Neuron, 24(1), 11–17.Google Scholar
Wolfe, J.M., Horowitz, T.S. (2017). Five factors that guide attention in visual search. Nat Hum Behav, 1, 0058.Google Scholar
Wolfe, J.M., Cave, K.R., Franzel, S.L. (1989). Guided search: an alternative to the feature integration model for visual search. J Exp Psychol: Hum Percept Perform, 15, 419–433.Google Scholar
Wolfe, J.M., Palmer, E.M., Horowitz, T.S. (2010). Reaction time distributions constrain models of visual search. Vision Res, 50, 1304–1311.Google Scholar
Wolfe, J.M., Vo, M.L.-H., Evans, K.K., Greene, M.R. (2011). Visual search in scenes involves selective and non-selective pathways. Trends Cogn Sci, 15(2), 77–84.Google Scholar
Zheng, B., Sumkin, J.H., Zuley, M.L., Wang, X., Klym, A.H., Gur, D. (2012). Bilateral mammographic density asymmetry and breast cancer risk: a preliminary assessment. Eur J Radiol, 81(11), 3222–3228.CrossRefGoogle Scholar

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