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Medical Image Analysis by Cognitive Information Systems – a Review

  • Patient Facing Systems
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Abstract

This publication presents a review of medical image analysis systems. The paradigms of cognitive information systems will be presented by examples of medical image analysis systems. The semantic processes present as it is applied to different types of medical images. Cognitive information systems were defined on the basis of methods for the semantic analysis and interpretation of information – medical images – applied to cognitive meaning of medical images contained in analyzed data sets. Semantic analysis was proposed to analyzed the meaning of data. Meaning is included in information, for example in medical images. Medical image analysis will be presented and discussed as they are applied to various types of medical images, presented selected human organs, with different pathologies. Those images were analyzed using different classes of cognitive information systems. Cognitive information systems dedicated to medical image analysis was also defined for the decision supporting tasks. This process is very important for example in diagnostic and therapy processes, in the selection of semantic aspects/features, from analyzed data sets. Those features allow to create a new way of analysis.

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References

  1. Alickovic, E., Subasi, A., Medical decision support system for diagnosis of heart arrhythmia using DWT and random forests classifier. J. Med. Syst. 2016.

  2. Hachaj, T., Ogiela, M.R., CAD system for automatic analysis of CT perfusion maps. Opto-Electronics Review. 19(1):95–103, 2011.

    Article  Google Scholar 

  3. Ogiela, L., Cognitive Computational Intelligence in Medical Pattern Semantic Understanding. In: Guo M.Z. et al. (Eds.), ICNC 2008, 4th International Conference on Natural Computation (ICNC 2008), Jian, PEOPLES R CHINA, October 18–20, vol. 6, Proceedings, pp. 245–247, 2008.

  4. Ogiela, L., Computational Intelligence in Cognitive Healthcare Information Systems. In: Bichindaritz, I., Vaidya, S., Jain, A. et al. (Eds.), Computational Intelligence in Healthcare 4: Advanced Methodologies, Studies in Comutational Intelligence, vol. 309, pp. 347–369, 2010.

  5. Ogiela, L., Semantic Analysis in Cognitive UBIAS & E-UBIAS Systems. Computers and Mathematics with Applications, vol. 63(2), Elsevier, pp. 378–390, 2012.

  6. Ogiela, L., Semantic analysis and biological modeling in selected classes of cognitive information systems. Mathematical and Computer Modelling 58:1405–1414, 2013.

    Article  Google Scholar 

  7. Ogiela, L., Cognitive informatics in image semantics description, identification and automatic pattern understanding. Neurocomputing. 122:58–69, 2013.

    Article  Google Scholar 

  8. Ogiela, L., Ogiela, M.R., Cognitive systems and bio-inspired computing in homeland security. Journal of Network and Computer Applications 38:34–42, 2014.

    Article  Google Scholar 

  9. Ogiela, M. R., Ogiela, L., Cognitive Informatics in Medical Image Semantic Content Understanding. In: Kim, T. H., Stoica, A., Chang, R.S. (Eds.), Security-Enriched Urban Computing and Smart Grid, Communications in Computer and Information Science, vol. 78, pp. 131–138, 2010.

  10. Ogiela, M.R., Ogiela, L., Towards New Classes of Intelligent Cognitive Information Systems for Semantic Pattern Classifications. Computing and Informatics 30(6):1099–1114, 2011.

    Google Scholar 

  11. Ogiela, M. R., Ogiela, U., Linguistic Extension for Secret Sharing (m, n)-threshold Schemes. SECTECH 2008 International Conference on Security Technology, Hainan Isl., China, pp. 125–128, 2008.

  12. Ogiela, M. R., Ogiela, U., Security of Linguistic Threshold Schemes in Multimedia Systems. In: Damiani, E., Jeong, J., Howlett, R.J. et al. (Eds.), New Directions in Intelligent Interactive Multimedia Systems and Services 2, Studies in Computational Intelligence, vol. 226, pp. 13–20, 2009.

  13. Ogiela, M. R., Ogiela, U., Shadow Generation Protocol in Linguistic Threshold Schemes. In: Slezak, D., Kim, T.H., Tang, W.C. et al. (Eds.), Security Technology, Communications in Computer and Information Science, vol. 58, pp. 35–42, 2009.

  14. Peker, M. A decision support system to improve medical diagnosis using a combination of k-medoids clustering based attribute weighting and SVM. J. Med. Syst. 2016.

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Acknowledgment

This work has been supported by the National Science Centre, Republic of Poland, under project number DEC-2013/09/B/HS4/00501.

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Correspondence to Lidia Ogiela.

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This article is part of the Topical Collection on Patient Facing Systems

Highlights

• It was present a cognitive systems for semantic data analysis.

• Proposed an semantic analysis for cognitive data interpretation and analysis.

• Examples of cognitive interpretation processes for medical image understanding was described.

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Ogiela, L., Takizawa, M. Medical Image Analysis by Cognitive Information Systems – a Review. J Med Syst 40, 212 (2016). https://doi.org/10.1007/s10916-016-0566-6

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  • DOI: https://doi.org/10.1007/s10916-016-0566-6

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