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First steps towards a blackboard controlled system for matching image and model in the presence of noise and distortion

  • Computer Vision
  • Conference paper
  • First Online:
Pattern Recognition (PAR 1988)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 301))

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Abstract

In this paper we discuss some of the problems of computer interpretation of medical ultrasound images and the use of an expert system to control the image processing and model matching. We describe an expert system shell developed for this task and detail our preliminary application to an ultrasound scan. We model the anatomical and geometric structures involved as a network of frames. This and the model-matching control strategy we have employed are discussed. An example of how the strategy operates is given with reference to example images and attention is drawn to the feedback aspects of the control mechanism. Finally, possible improvements and enhancements to the work are considered.

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7. Bibliography

  • Baldock R.A., J. Ireland and S.J. Towers, “SBS User Guide”, MRC CAPCU internal report (1987a)

    Google Scholar 

  • Baldock R.A., J. Ireland and S.J. Towers, “A Pilot Study of Knowledge-Based Control for Image Processing”, MRC CAPCU internal report (1987b)

    Google Scholar 

  • Ballard D.H. and C.M. Brown, “Computer Vision” (Prentice-Hall, New Jersey; 1982)

    Google Scholar 

  • Brooks R.A., “Symbolic Reasoning Among 3-D Models and 2-D Images”, Artificial Intelligence 17 (1981) 285–348

    Article  Google Scholar 

  • Clark P., “Rule-Based Systems in Image Processing”, Turning Institute report (1987) unpublished.

    Google Scholar 

  • Ensor J.R. and J.D. Gabbe, “Transactional Blackboards” Art. Intell. in Eng. 1 (1986) 80–84

    Article  Google Scholar 

  • Erman J.R., F. Hayes-Roth, V.R. Lesser and R. Reddy, “The Hearsay-II Speech Understanding System: Integrating Knowledge to Resolve Uncertainty”, ACM Computing Surveys 12 (1980) 213–253

    Article  Google Scholar 

  • Fisher R.B. and M.J.L. Orr, “Solving Geometric Constraints in a Parallel Network”, Proc. of 3rd Alvey Vision Conf., Cambridge (1987) 87–95

    Google Scholar 

  • Hayes-Roth B., “A Blackboard Architecture for Control”, Artificial Intelligence 26 (1985) 251–321

    Article  Google Scholar 

  • Minsky M., “The Psychology of Computer Vision” ed P. Winston (McGraw Hill, NY; 1975)

    Google Scholar 

  • Nii H.P. and E.A. Fiegenbaum, “Rule-Based Understanding of Signals in Pattern Directed Inference Systems” (Academic Press; 1978)

    Google Scholar 

  • Orr M.J.L. and R.B. Fisher, “Geometric Reasoning for Computer Vision”, Image and Vision Computing 5 (1987) 233–238

    Article  Google Scholar 

  • Rake S.T. and L.D.R. Smith, “The Interpretation of X-ray Angiograms using a Blackboard Control Architecture”, Proceedings of the Symposium on Computer Assisted Radiology (Springer-Verlag, Berlin; 1987) to be published

    Google Scholar 

  • Russell G.T. and D.M. Lane, “A Knowledge-Based System Framework for Environmental Perception in a Subsea Robotics Context”, IEEE J. of Oceanic Eng. OE-11 (1986) 401–412

    Article  Google Scholar 

  • Towers S.J., “Frames as Data Structures for SBS”, MRC CAPCU internal report (1987)

    Google Scholar 

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J. Kittler

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© 1988 Springer-Verlag Berlin Heidelberg

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Baldock, R., Towers, S. (1988). First steps towards a blackboard controlled system for matching image and model in the presence of noise and distortion. In: Kittler, J. (eds) Pattern Recognition. PAR 1988. Lecture Notes in Computer Science, vol 301. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-19036-8_43

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  • DOI: https://doi.org/10.1007/3-540-19036-8_43

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-19036-3

  • Online ISBN: 978-3-540-38947-7

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