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Lung tumor segmentation using improved region growing algorithm

  • Soltani-Nabipour, Jamshid (Medical Radiation Engineering Department, Islamic Azad University) ;
  • Khorshidi, Abdollah (School of Paramedical, Gerash University of Medical Sciences) ;
  • Noorian, Behrooz (Nuclear Engineering Department, Faculty of Electrical and Computer Engineering, Graduate University of Advanced Technology)
  • Received : 2019.12.24
  • Accepted : 2020.03.11
  • Published : 2020.10.25

Abstract

The goal of this project is to achieve an accurate segmentation of the pulmonary tumors besides shortening the time and increasing the accuracy. Here, improved region growing (IRG) algorithm is introduced in order to segment the lung tumor with a sufficient accuracy in a shorter time compared to the other basics methods. This comprehensive algorithm was applied on 4 patients CT images and the results of the various steps on segmentation improvement shown 98% accuracy as compared to the basic algorithm. The combination of "multipoint growth start" produced a desirable outcome in accurately bounding the tumor. The proposed algorithm improved tumor identification by less than 13% along with a sufficient percentage of compliance accuracy.

Keywords

References

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