03 آذر 1403
فاطمه صادقي

فاطمه صادقی

مرتبه علمی: مربی
نشانی: دانشکده مهندسی جم - گروه مهندسی صنایع (جم )
تحصیلات: کارشناسی ارشد / مهندسی صنایع
تلفن: 077
دانشکده: دانشکده مهندسی جم

مشخصات پژوهش

عنوان Detection of lung cancer using CT image based on novel PSO clustering
نوع پژوهش مقالات در نشریات
کلیدواژه‌ها
lung cancer, image clustering, PSO clustering
مجله Journal of Industrial and Systems Engineering
شناسه DOI IIEC14_061
پژوهشگران فاطمه صادقی (نفر اول) ، عباس احمدی (نفر دوم)

چکیده

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.