Diagnosis of Liver Cancer by Fuzzy Kmeans Clustering Based on Evidence Theory

International Journal of Smart Electrical Engineering

دوره 11، شماره 03، آذر 2022، صفحه 119-129   

نوع مقاله: Research Paper

شناسه دیجیتال (DOI): 10.30495/ijsee.2022.1948054.1163

نویسندگان

Babak Fouladi Nia¹؛ Abbas Karimi^{* 1}؛ Faraneh Zarafshan²؛ Manochehr Kazemi³

¹Department of Computer Engineering, Arak Branch, Islamic Azad University, ARAK, Iran

²Department of Computer Engineering, Ashtian Branch, Islamic Azad University, Ashtian, Iran

³Department of Mathematics, Ashtian Branch, Islamic Azad University, Ashtian, Iran

چکیده

Liver cancer is one of the most common cancers that causes many deaths every year. In recent years, the risk of men and women getting liver cancer has increased by 40% and 23%, respectively. In order to identify a tumor in the liver, segmentation is performed on CT images. The use of data fusion methods in data mining techniques is one of the most practical methods to improve accuracy, which also has many applications in the field of medical image processing. Correct and efficient diagnosis of liver abnormalities leads to a significant reduction in human error and a more accurate diagnosis by physicians. This requires the use of methods based on automatic and semi-automatic detection. Combining clustering methods and considering cluster uncertainty is an appropriate tool in solving clustering problems in medical image processing, especially cancer diagnosis. The proposed method, in addition to having high accuracy, has a high convergence speed.

کلیدواژه‌ها

Liver cancer؛ Evidence theory؛ Fuzzy system؛ KMEANS clustering

سایر فایل های مرتبط با مقاله

vol11-no3-p2.pdf