A system to model, assist and control the human observation of microscopic specimen

  • A. Derder
  • C. Garbay
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 753)


This paper describes current research on computerized assistance to cytological specimen exploration. The purpose is not to design a new diagnosis expert system, but rather to design a system able to cooperate with the human expert in the execution of specimen exploration task. New man machine assistance models are necessary to this end, which imply not only knowledge-based but also behaviour-based modelling. An information manager is described, allowing access to information supplied by this model. An error monitoring is also presented. Its goal is to control all tasks and activities involved in the cytological specimen exploration.


Expert System Task Model Finite State Automaton Error Monitoring Syntactical Parser 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    G. Brugal, R. Dye, B. Krief, J.M. Chassery, H. Tanke and J.H. Tucker: HOME: Highly Optimized Microscope Environment. Cytometry, Vol. 13, pp. 109:116 (1992).Google Scholar
  2. 2.
    Bartels & al.: Expert Systems in Histopathology, Anal. Quant. Cytol. 11(1):1–7 (1989)Google Scholar
  3. 3.
    Ovalle, A. & Garbay, C.: KIDS, a Distributed Expert System for Biomedical Image Interpretation. 12th International Conference on IPMI, pp. 419–433. Colchester et Hawkes (Eds), Springer-Verlag (1991)Google Scholar
  4. 4.
    D. D. Woods, L. Johannesen and S. S. Potter: Human Interaction with Intelligent System: An Overview and Bibliography. SIGART Bulletin, Vol. 2, No 5, pp. 39–50 (1987)Google Scholar
  5. 5.
    E. M. Roth, K. B. Bennett and D.D. Woods: Human Interaction with “Intelligent” Machine. Internationaml Man-Machine Studies, pp. 479–525 (1987)Google Scholar
  6. 6.
    E. Hudlicka, K Corber, R. Schudy, and S. Baron: Flight crew aiding for recovery from subsystem failures. Technical Repport NASA Contractor Repport 181905, Bolt, Beranek and New-man (1990)Google Scholar
  7. 7.
    M. Gonzalez and S. Faure: Des Conditions d'utilisation d'un système d'aide à la decision médicale, Psychologie Cognitive Modèles et Methodes, P.U.G., 1988Google Scholar
  8. 8.
    W. B. Rousse: Adaptive aiding for human/computer control. Human Factors, 30:431–443 (1988)Google Scholar
  9. 9.
    Chandrasekaran, B.: Towards a functional architecture for intelligence based on generic information processing tasks. Proc. 10th IJCAI, pp. 1183–1192 (1987)Google Scholar
  10. 10.
    O. Raoult: Diagnostic de pannes des systemes complexes.Thèse de Docteur de l'I.N.P.G. (France) (1989)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • A. Derder
    • 1
  • C. Garbay
    • 1
  1. 1.Equipe Reconnaissance des Formes et Microscopie Quantitative Lab. TIM3 / IMAGUniversité Joseph FourierGrenoble CedexFrance

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