Hybrid Fuzzy Models and Experimental-based Collective Intelligence Algorithms for Detection of Breast Tumors through Mammography Image Analysis

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Khodadadi Elnaz; HOSSEINI RAHIL; MAZINANI MAHDI

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Journal: COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING) Year:2021 | Volume:12 | Issue:1 Page(s): 99-122

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Information Journal Paper

Title

Hybrid Fuzzy Models and Experimental-based Collective Intelligence Algorithms for Detection of Breast Tumors through Mammography Image Analysis

Author(s)

Khodadadi Elnaz | HOSSEINI RAHIL | MAZINANI MAHDI | Issue Writer Certificate

Keywords

Fuzzy Inference System

Breast Tumors

Benign

Malignant

Soft Computing

Evolutionary Hybrid Algorithms

Abstract

In this study, a hybrid fuzzy intelligent method for diagnosing and managing uncertainty in input features to identify Breast Tumors in mammography images has been proposed. Moreover, a hybrid fuzzy evolutionary model has been applied to increase the system efficiency and optimize results. Soft Computing models were used to detect the type of breast mass based on the analysis of features in mammography images. The combined models proposed in this study include FuzzyTBO and Fuzzy-PSO-TLBO models. The performance evaluation was conducted using the Receiver Operator Characterization (ROC) analysis in terms of accuracy and area under the ROC curve. A 10-fold cross-validation technique was conducted to divide the data into training and testing sections. The obtained results reveal an accuracy of 96. 27% for determining different types of mass based on tumors’ features according to the images. The presented model competes and outperforms other proposed models in previous studies. The outcome of this study may be promising for apropos diagnosis and effective treatments.

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APA: Copy

Khodadadi, Elnaz, HOSSEINI, RAHIL, & MAZINANI, MAHDI. (2021). Hybrid Fuzzy Models and Experimental-based Collective Intelligence Algorithms for Detection of Breast Tumors through Mammography Image Analysis. COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING), 12(1 ), 99-122. SID. https://sid.ir/paper/954965/en

Vancouver: Copy

Khodadadi Elnaz, HOSSEINI RAHIL, MAZINANI MAHDI. Hybrid Fuzzy Models and Experimental-based Collective Intelligence Algorithms for Detection of Breast Tumors through Mammography Image Analysis. COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING)[Internet]. 2021;12(1 ):99-122. Available from: https://sid.ir/paper/954965/en

IEEE: Copy

Elnaz Khodadadi, RAHIL HOSSEINI, and MAHDI MAZINANI, “Hybrid Fuzzy Models and Experimental-based Collective Intelligence Algorithms for Detection of Breast Tumors through Mammography Image Analysis,” COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING), vol. 12, no. 1 , pp. 99–122, 2021, [Online]. Available: https://sid.ir/paper/954965/en

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