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Medical Image Processing: A Brief Survey and a New Theoretical Hybrid ACO Model

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Combinations of Intelligent Methods and Applications

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 46))

Abstract

The current paper includes a brief survey on image processing, in particular for medical image processing, including the main algorithms on segmentation and margin detection. Both mathematical background and algorithms are detailed. Some of the most efficient ant-based algorithms used for image processing are also described. It is also introduced a new theoretical hybrid Ant Colony Optimization model in order to enhance medical image processing. The newly introduced model uses artificial ants with different levels of “sensitivity” and also a model of “direct” communication as in Multi-Agent Systems.

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Author information

Authors and Affiliations

  1. Faculty of Sciences, TU Cluj-Napoca, Cluj-napoca, Romania

    Camelia-M. Pintea & Cristina Ticala

Authors
  1. Camelia-M. Pintea
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  2. Cristina Ticala
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Corresponding author

Correspondence to Camelia-M. Pintea .

Editor information

Editors and Affiliations

  1. Sch of Engg, Dept of Comp Engg & Informa, University of Patras, Patras, Greece

    Ioannis Hatzilygeroudis

  2. Faculty of Eng & Comp, E&C bldg, Coventry University, Coventry, United Kingdom

    Vasile Palade

  3. Dept of Edu Sci Early child, Lab of info, Democritus Univer Thrace,Sch of Edu Sci, Alexandroupolis, Greece

    Jim Prentzas

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Pintea, CM., Ticala, C. (2016). Medical Image Processing: A Brief Survey and a New Theoretical Hybrid ACO Model. In: Hatzilygeroudis, I., Palade, V., Prentzas, J. (eds) Combinations of Intelligent Methods and Applications. Smart Innovation, Systems and Technologies, vol 46. Springer, Cham. https://doi.org/10.1007/978-3-319-26860-6_7

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  • DOI: https://doi.org/10.1007/978-3-319-26860-6_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26858-3

  • Online ISBN: 978-3-319-26860-6

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