Early Diagnosis of Lung Cancer Using Computer Aided Detection via Lung Segmentation Approach

Early Diagnosis of Lung Cancer Using Computer Aided Detection via Lung Segmentation Approach

  IJETT-book-cover           
  
© 2021 by IJETT Journal
Volume-69 Issue-5
Year of Publication : 2021
Authors : Abhir Bhandary, Ananth Prabhu G, Mustafa Basthikodi, Chaitra K M
DOI :  10.14445/22315381/IJETT-V69I5P213

How to Cite?

Abhir Bhandary, Ananth Prabhu G, Mustafa Basthikodi, Chaitra K M, "Early Diagnosis of Lung Cancer Using Computer Aided Detection via Lung Segmentation Approach," International Journal of Engineering Trends and Technology, vol. 69, no. 5, pp. 85-93, 2021. Crossref, https://doi.org/10.14445/22315381/IJETT-V69I5P213

Abstract
Lung cancer begins in the lungs and leading to the reason of cancer demise amid population in the creation. According to the American Cancer Society, which estimates about 27% of the deaths because of cancer. In the early phase of its evolution, lung cancer does not cause any symptoms usually. Many of the patients have been diagnosed in a developed phase where symptoms become more prominent, that results in poor curative treatment and high mortality rate. Computer Aided Detection systems are used to achieve greater accuracies for the lung cancer diagnosis. In this research exertion, we proposed a novel methodology for lung Segmentation on the basis of Fuzzy C-Means Clustering, Adaptive Thresholding, and Segmentation of Active Contour Model. The experimental results are analysed and presented.

Keywords
Computer Aided Detection, Diagnosis, Fuzzy clustering, Lung cancer, Segmentation, Thresholding

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