Microwave Imaging System of Breast Cancer Detection by Using Support Vector Machine Method

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Azhar Albaaj
Yaser Norouzi
Gholamreza Moradi


Breast Cancer, Classification, Microwave imaging, Support Vector Machine


Breast cancer is the most common disease among women in the world. Therefore, many doctors diagnose cancer in its early stages. Because early detection and treatment of the tumor help in faster recovery. The main objective of this paper is to build an application that is capable of “detecting and determining” a breast tumor using image processing in MATLAB. An open-source experimental database of the University of Manitoba Breast Microwave Imaging Dataset (UM-BMID) was used. The most vital part is template design and the formation of the algorithm for breast tumor detection. Some of the key features used in this paper are - image acquisition, noise reduction, image resizing, tumor region identification, marking of tumors, etc. A Graphical User Interface (GUI) is also used to build a better interface for the user, it allows us to understand the algorithm's true potential and how it can be further developed due time. After an image is provided to the algorithm it processes the image and informs the user how harmful the tumor is to the patient, and what necessary steps should she take to find a cure for it. In this work, Support Vector Machines (SVM) were used to detect breast cancer using microwave imaging. We extract features from the data collected by microwave imaging and use SVM to classify them. This work can help to support microwave breast imaging as well as help to move away from false positives to obtain greater accuracy and detect tumors depicted as false negatives.

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