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ILTDS: Intelligent Lung Tumor Detection System on CT Images

  • Kamil Dimililer
  • Yoney Kirsal Ever
  • Buse Ugur
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 530)

Abstract

Cancer detection and research on early detection solutions play life sustaining role for human health. Computed Tomography images are widely used in radiotherapy planning. Computed Tomography images provide electronic densities of tissues of interest, which are mandatory. For certain target delineation, the good spatial resolution and soft/hard tissues contrast are needed. Also, Computed Tomography techniques are preferred compared to X-Ray and magnetic resonance imaging images. Image processing techniques have started to become popular in use of Computed Tomography images. Artificial neural networks propose a quite different approach to problem solving and known as the sixth generation of computing. In this study, two phases are proposed. For first phase, image pre-processing, image erosion, median filtering, thresholding and feature extraction of image processing techniques are applied on Computed Tomography images in detail. In second phase, an intelligent image processing system using back propagation neural networks is applied to detect lung tumors.

Keywords

Intelligent Systems Digital Image Processing Artificial Neural Networks CT Lung Cancer Images Thresholding Feature Extraction 

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Kamil Dimililer
    • 1
  • Yoney Kirsal Ever
    • 2
  • Buse Ugur
    • 3
  1. 1.Electrical and Electronic Engineering Department, Faculty of EngineeringNear East UniversityNicosiaCyprus
  2. 2.Software Engineering Department, Faculty of EngineeringNear East UniversityNicosiaCyprus
  3. 3.Biomedical Engineering Department, Faculty of EngineeringNear East UniversityNicosiaCyprus

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