Digital Mammogram Inferencing System Using Intuitionistic Fuzzy Theory  

作　　者：Susmita Mishra M.Prakash 

机构地区：[1]Department of CSE,Rajalakshmi Engineering College,Chennai,India [2]Karpagam College of Engineering,Coimbatore,India

出　　处：《Computer Systems Science & Engineering》2022年第6期1099-1115,共17页计算机系统科学与工程（英文）

摘　　要：In the medical field,the detection of breast cancer may be a mysterious task.Physicians must deduce a conclusion from a significantly vague knowledge base.A mammogram can offer early diagnosis at a low cost if the breasts'satisfactory mammogram images are analyzed.A multi-decision Intuitionistic Fuzzy Evidential Reasoning(IFER)approach is introduced in this paper to deal with imprecise mammogram classification efficiently.The proposed IFER approach combines intuitionistic trapezoidal fuzzy numbers and inclusion measures to improve representation and reasoning accuracy.The results of the proposed technique are approved through simulation.The simulation is created utilizing MATLAB software.The screening results are classified and finally grouped into three categories:normal,malignant,and benign.Simulation results show that this IFER method performs classification with accuracy almost 95%compared to the already existing algorithms.The IFER mammography provides high accuracy in providing early diagnosis,and it is a convenient diagnostic tool for physicians.

关 键 词：MAMMOGRAM intuitionistic fuzzy evidential reasoning trapezoidal fuzzy MALIGNANT BENIGN 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]