Skip to main content
SpringerLink
Log in

Improved observer dependent perception of weak edges when scanning an image in real time indicated by introducing 1/f noise into the primary visual cortex V1. Theory and experimental support

  • Scientific Papers
  • Published:
Australasian Physics & Engineering Sciences in Medicine Aims and scope Submit manuscript

Abstract

We present results of a new process for generating 1/f type noise sequences and introducing the noise in the primary visual cortex which then enables improved perception of weak edges when an observer is scanning a complex image in real time to detect detail such as in mammogram reading sessions. It can be explained by an adaptation of information theory for functional rather than previous task-based methods for formulating processes for edge formation in early vision. This is enabled from a two “species” classification of the interaction of opposing on-centre and off-centre neuron processes. We show that non-stationary stochastic resonances predicted by theory can occur with 1/f noise in the primary visual cortex V1 and suggest that signalling exchanges between V1 and the lateral geniculate nucleus (LGN) of the thalamus can initiate neural activity for saccadic action (and observer attention) for weak edge perception. Improvements predicted by our theory were shown from 600 observations by two groups of observers of limited experience and an experienced radiologist for reference (but not for diagnosis). They scanned and rated the definition of microcalcification in clusters separately rated by the experienced radiologist. The results and supporting theory showed dependence on the observer’s attention and orderly scanning. Using a compact simplified equipment configuration the methodology has important clinical applications for conjunction searches of features and for detection of objects in poor light conditions for vehicles.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Hung, W., Nguyen, H., Lee, W., Rickard, M., Thornton, B. and Blinowska, A.,Diagnostic abilities of three CAD method for assessing microcalcifications in mammograms and an aspect of equivocal cases decisions by radiologists, Australas. Phys.Eng. Sci. Med. 26, 78–83, 2003.

    Article  Google Scholar 

  2. Kitajo, K., Nozaki, D., Ware, L.M. and Yamamoto, Y.,Behavioural stochastic resonance within the human brain, Phys Rev Lett, 90, 218103–4, 2003.

    Article  PubMed  Google Scholar 

  3. Arnold, L., Horsthemke, W. and Stuki, J.,The influence of external real and white noise on the Lotka-Volterra model, Biomed Jl 21, 451–471, 1979.

    Google Scholar 

  4. Sommer, M.A. and Wurtz. R.H.,Influence of the thalamus on spatial visual processing in frontal cortex, Nature, 444, 374–377.

  5. Dror, G. and Tso dyk,Analysis and modelling of population dynamics in the visual cortex, Neurocomputing, 26–27, 361–366, 1999.

    Article  Google Scholar 

  6. Kobayashi, M. and Musha, T., 1/f fluctuations of heartbeat period, IEEE, Trans. Biomed. Eng., 29, 456–457, 1982.

    Article  CAS  Google Scholar 

  7. Demanude, C., James, C., Sonuga-Bark, E., Kobayashi, M. and Musha, T.,Distinguishing low frequency oscillations within the 1/f spectral behaviour of electromagnetic brain, IEEE Trans. Biomed. Eng, 29, 456–457, 1982.

    Article  Google Scholar 

  8. Pillow, J., Shlens, J., Paninski, L., Sher, A., Litke, A., Chichiliniksky, E. and Simoncelli, E.,Spatio-temporal correlations and visual signalling in complete neuronal population, Nature 07140 on line 23 July, 2008

  9. Murray, J.R.,Mathematical Biology, ch.3, Springer-Verlag, New York, 2002.

    Google Scholar 

  10. Siegel, R.M.,Non-linear dynamical system theory and primary visual cortical processing, Physica, D 42, 385, 1990.

    Article  Google Scholar 

  11. Sirovitch, L., Everson, R., Kaplan, E., Knight, B. and Orbach, D.,Modelling the functional organisation of the visual cortex, Physica D96, 355–366, 1996.

    Article  Google Scholar 

  12. Logan, B.,Information in the zero crossings of bandpass signals, Bell Sys. Tech. J. 56, 4, 187–217, 1980.

    Google Scholar 

  13. Caldwell, C., Stapleton, S., Holdsworth, D., Jong, R., Weisert, W., Cooke, G. and Yaffe, M.,Characterisation of mammographic parenchymal pattern by fractal dimensions, Phys, Med. Biol. 35, 235–247, 1990.

    Article  CAS  Google Scholar 

  14. Sano, M., Nakauchi, H., Akabane, H. and Musha, T.,Model study of spontaneous discharge of a membrane potential, Japan J. Appl. Physics 29, 2186–2190, 1990.

    Article  Google Scholar 

  15. Furukawa, H.,Universal spectra of quasirandom objects produced by off-equilibrium space divisions, Phys. Rev., A34, 2315–2323, 2000.

    Article  Google Scholar 

  16. Jensen, H.,Lattice gas as a model of 1/f noise, Phys. Rev. Lett., 90, 218103–4, 1989.

    Google Scholar 

  17. Crandell, R.E.,Projects in Scientific Computation, Sections 5 and 6, Springer-Verlag, New York, 1994.

    Google Scholar 

  18. Al Bayyati, H.A.,A rule of thumb for determining a sample size in comparing two properties, Technometrics 13, 75–77, 1971.

    Article  Google Scholar 

  19. Diem, K. and Seldru, P.J.,Scientific Tables, Vol. 2, 193–4, Ed. C. Lentner, Ciba-Geigy, Basle, Switzerland, 1982.

    Google Scholar 

  20. Pinneo, L.R.,Visual prosthesis by electrical stimulation of primary visual pathways in Visual Prothesia, The Interdisciplinary Dialogue, 109–127 (Ed. Sterling et al), Academic Press, 1971.

  21. Murch, G., Visual and Auditory Perception, The Bobb-Merrill Co Inc. Indianapolis, 1973.

    Google Scholar 

  22. Beam, C., Layde, P. and Sallison, D.,Variability in interpretation of screening mammograms by US radiologists. Finding from a national sample, Achiv. Internal Medicine, 156, 20099–213, 1996.

    Google Scholar 

  23. Resigno, A. and Maccacaro, G.A.The Information Content of Biological Classifications, in Information Theory, (ed. Colin Cherry), Butterworths, London, 437–446, 1961.

    Google Scholar 

  24. Gilbert, E.,Information Theory and continued by Quastler, H., for Biological applications of Information Theory in Encylopaedia of Science & Technology Vol. 5, 101 and 113–114, McGraw-Hill, New York, 1979.

    Google Scholar 

  25. Geisler, W.S. and Banks, M.S.,Retinal Processing in Handbook of Optics, Vol. 1 25.10–13, (Eds. Bass, M., et al), McGraw-Hill, New York, 1995.

    Google Scholar 

  26. Zeki, Z.A Vision of the Brain, Blackwell Scientific Publications, Oxford, 1993.

    Google Scholar 

  27. Marr, D. and Hildreth, E.,Theory of edge detection, Proc. Roy. Soc., London, B2007, 187–217, 1980.

    Article  Google Scholar 

  28. Grussser, O.-J. and Grusser-Coornehls, U.,The Sense of Sight in Human Physiology, Second Revised Edition, Springer-Verlag, Berlin, 237–276, 1987.

    Google Scholar 

  29. Roska, B., Molnar, A. and Werblin, F.S.Parallel processing in retinal ganglion, cells: How integration of space-time patterns of excitation and inhibition form the spiking output, J. Neurophysiol., 95, 3810–3822, 2006.

    Article  PubMed  Google Scholar 

  30. Baylor, D. and Fuortes, M.Electrical responses of single cones in the retina of the turtle, Jl. Physiology, London, 207, 77, 1970.

    Google Scholar 

  31. Thornton-Benko, E.,PhD Thesis, Neurological Modelling of the Vision System with Relevance to an Application for Improved Detection of Early Breast Cancer. Faculty of Science, University of Technology Sydney, 2005.

    Google Scholar 

  32. Bohner, D. and Paterson, A.,Discrete Equations on Time Scales. An Introduction with Applications, Ch. 1., Birkhauser, Basel, Switzerland, 2001.

    Google Scholar 

  33. Qian, Y., Xianghn, Q. and Weing, Y.,Modelling neuronal dynamic coding in primary visual cortex, Biosystems, 58, 203–209, 2000.

    Article  Google Scholar 

  34. Shams, I. and Von der Malsburt,The Role of complex cells in object recognition, Vision Research, 42, 2547–2554, 2002.

    Article  PubMed  Google Scholar 

  35. Crick, F.,The Astonishing Hypothesis, The Scientific Search for the Soul, 134, Simon & Schuster, New York, 1994.

    Google Scholar 

  36. Wandell, B.A.,Foundations of Vision, ch. 10, Sinauer Associates, Sunderland, Massachusets, 1996.

    Google Scholar 

  37. Koch. C.,Biophysics of Computation, Oxford Univ. Press. Oxford, 1999.

    Google Scholar 

  38. Farley, B. and Clark, W.A.,Activity in networks of neuron-like elements, in Information Theory, (Ed. Colin Cherry), Butterworths, London, 1961.

    Google Scholar 

  39. Dudkin, K.N.,Cooperative neural networks underlying image description in visual cortex, IEEE Symposium on Neuroinformatics and Neurocomputers, 7–10, Vol 1, 387–398, 1992.

    Article  Google Scholar 

  40. Malach, R., Avidan , G., Lerner, Y., Hansen, U. and Levy, I.,The cartography of human visual object areas, Ch 9 in Functional Neuroimaging of Visual Cognition, (Ed N. Kanwisher & J. Duncan), Oxford University Press, 2003.

  41. Syme, S., Oppwood, R., Mallot, H., Mason, S. and Zrenner, E.,Mimicking the brain, Physics World, 15, 31, 2002.

    Google Scholar 

  42. Dror, G. and Tso dyk,Analysis and modelling of population dynamics in the visual cortex, Neurocomputing, 26–27, 361–366, 1999.

    Article  Google Scholar 

  43. Carandini, M., Heeger, D. and Senn, W.,Asynaptic explanation of suppression in visual cortex, Jl of Neuroscience, 22, 1053–1065, 2002.

    Google Scholar 

  44. Blackmore, C. and Campbell, F.W.,On the existence of neurons in the human visal system selectivity sensitive to the orientation and size of retinal images, J. Physiol., 203, 237–260, 1969.

    Google Scholar 

  45. Beierlein, M., Fall, C.P., Rinzel, J. and Yuste, R.,Thalamocortical bursts trigger recurrent activity in neocortical networks: layer 4 as a frequency-dependent gate, Jl of Neuroscience, 22, 237–260, 2002.

    Google Scholar 

  46. Higgins, G. and Wolf, R.,The relation of definition to sharpness and resolving power as a photographic system, Jl Opt. Soc. Am., 45, 121–129, 1995.

    Article  Google Scholar 

  47. Fakir, R.,Nonstationary stochastic resonance, Phys. Rev. E., 57, 6996–7001, 1998.

    Article  CAS  Google Scholar 

  48. Rolls, E. and Deco, G.,Computational Neuroscience of Vision Appendix B, Oxford Univ. Press, Oxford, 2004.

    Google Scholar 

  49. Schall, J.D.,Neural selection and control of action. Functional Neuroimaging of Visual Cognition, Attention and Performance, ch.20 (Ed. Kanwisher, N. and Duncan, J.), Oxford Univ. Press Oxford, 2004.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Royal Prince Alfred Hospital, Camperdown, Sydney, Australia

    E. Thornton-Benko

  2. Key Centre for Health Technologies, University of Technology, Sydney, Australia

    H. T. Nguyen

  3. Breast Screen, New South Wales, Australia

    W. T. Hung

  4. School of Physics University of Sydney, Australia

    B. S. Thornton

  5. Department of Mathematics, University of Technology Sydney, Sydney, Australia

    B. S. Thornton

Authors
  1. E. Thornton-Benko
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. H. T. Nguyen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. W. T. Hung
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. B. S. Thornton
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to E. Thornton-Benko.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Thornton-Benko, E., Nguyen, H.T., Hung, W.T. et al. Improved observer dependent perception of weak edges when scanning an image in real time indicated by introducing 1/f noise into the primary visual cortex V1. Theory and experimental support. Australas. Phys. Eng. Sci. Med. 32, 136–149 (2009). https://doi.org/10.1007/BF03178641

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF03178641

Key words

Search

Navigation