November 23, 2024
fatemeh sadeghi

fatemeh sadeghi

Academic Rank: Instructor
Address:
Degree: M.Sc in Industrial Engineering
Phone: 077
Faculty: Jam Faculty of Engineering

Research

Title Detection of lung cancer using CT image based on novel PSO clustering
Type Article
Keywords
lung cancer, image clustering, PSO clustering
Journal Journal of Industrial and Systems Engineering
DOI IIEC14_061
Researchers fatemeh sadeghi (First researcher) , abbas ahmadi (Second researcher)

Abstract

Lung cancer is one of the most dangerous diseases that cause the large number of deaths. Early detection and analysis can be very helpful for successful treatment. Image segmentation plays a key role in the early detection and diagnosis of lung cancer. k-means algorithm and classic PSO clustering are the most common methods for segmentation that have poor outputs. In this article, we propose a new modified PSO method. The performance of proposed algorithm is compared to that of K-means and classic PSO clustering. The obtained results show that the new PSO clustering has better results as compared to the other methods. Comparison between the proposed method and classic PSO , in terms of fitness function and convergence of fitness function indicate that the proposed method is more effective in detecting lung cancer.