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Medical Image Thresholding Using Particle Swarm Optimization

  • Debashis Mishra
  • Isita Bose
  • Utpal Chandra De
  • Madhabananda Das
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 308)

Abstract

Image processing has been serving as one major part of medical science since 1980s as automation of image analysis offers better results in efficient time period to help specialists in diagnosis and eradication of diseases. Most frequently, medical fields face different cases of detecting tumors, kidney stones, fractures in bones, etc. through various images such as ultrasound images and X-ray images. But it is very difficult for identification of some particular structure in some medical images. Hence, such images need more improvement in terms of noise reduction and segmentation. Image thresholding is a kind of segmentation process which partitions the image into different objects. Particle swarm optimization (PSO) is one bio-inspired optimization technique which gets one optimized threshold value for image thresholding in this paper using proper fitness function.

Keywords

Swarm intelligence PSO Image processing Image segmentation Thresholds Image histogram Medical images 

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Copyright information

© Springer India 2015

Authors and Affiliations

  • Debashis Mishra
    • 1
  • Isita Bose
    • 1
  • Utpal Chandra De
    • 2
  • Madhabananda Das
    • 1
  1. 1.School of Computer EngineeringKIIT UniversityBhubaneswarIndia
  2. 2.School of Computer ApplicationKIIT UniversityBhubaneswarIndia

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