Early Detection of Lung Cancerby using Fuzzy Logic

  • Abstract
  • Keywords
  • References
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  • Abstract

    Lung Cancer is one of the heath challengesin the world it has been increased in the most of countries, so the early detection or diagnosis is most important issue to help the patients to recoverfrom the cancer.  In this paper we proposed a new algorithm for Lung cancer disease diagnosis by using Discrete Wavelet Transform (DWT) and Fuzzy logic, where our algorithm consist from five steps; the first step is for image acquisition; the second step is for image preprocessing (image enhancement and de-noising); the third step is for image analysis by using discrete wavelet transform (DWT); the fourth step is for features extraction (in our paper there are seven texture features used for detection), the final step is for classification  and diagnosis by using fuzzy logic to know wither the disease is cancer or not. The performance of our algorithm is gave high accuracy up to 97% in testing and 100% in training, by using 350 images from our collected database, we collected our database from Thi-Qar Heart Center, Iraq.




  • Keywords

    Lung Cancer; Image Enhancement;DWT, Feature Extraction; Detection, Fuzzy Logic.

  • References

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      [7] FALGUNI TANDEL, PRATIMA MORE. "Stability Indicating HPLC Method for Simultaneous Estimation of Nicotinamide and Salicylic Acid ." International Journal of Pharmacy Research & Technology 8 (2018), 43-47.

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      [10] Maryam Amiri1, Hamid Tavakolipour and Sepideh Gharehyakheh “Modeling of melon drying by application of microwave using mamdani fuzzy inference system” European Journal of Experimental Biology, Volume. 4, No.1, pp. 44-52, 2014.




Article ID: 27001
DOI: 10.14419/ijet.v7i4.25.27001

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