Comparison of lung CT images segmentation accuracy in patients with covid -۱۹ using K-means and Fuzzy C-means
Publish place: Fifth International Conference on Information Technology, Computer and Telecommunication Engineering of Iran
Publish Year: 1400
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ICTBC05_015
تاریخ نمایه سازی: 27 بهمن 1400
Abstract:
Image segmentation is a fundamental step to analyze images and extract data from them. Image segmentation is considered as most essential medical imaging process since it extracts the region of interest through a semi-automatic or automatic process. In this paper, two algorithms (i.e., K-means and Fuzzy C-means) have been used to segment the lung computed tomography (CT) images of patients with Covid-۱۹. Finally, the results of images segmentation are examined to measure the accuracy of the algorithms.
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Authors
Amin Alidoost Jehezdani
Faculty of Mathematics and Computer Science, Damghan University, Damghan, Iran.
Alireza Mehravin
Faculty of Mathematics and Computer Science, Damghan University, Damghan, Iran.
Seyed Hashem Tabasi
Faculty of Mathematics and Computer Science, Damghan University, Damghan, Iran.
Mostafa Zaare khormizi
Faculty of Mathematics and Computer Science, Damghan University, Damghan, Iran.