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shahalinejad S, Bahadori A, niapour A. Diagnosis of Breast Cancer Using the Harris Extraction Algorithm in the Processing of Medical Images. aumj 2022; 12 (1) :69-76
URL: http://aums.abzums.ac.ir/article-1-1625-en.html
URL: http://aums.abzums.ac.ir/article-1-1625-en.html
Diagnosis of Breast Cancer Using the Harris Extraction Algorithm in the Processing of Medical Images
1- Faculty of Electrical and Computer Engineering, Urumi Institute of Higher Education, Urmia, Iran
2- Faculty of Medicine, Ardabil University of Medical Sciences, Ardabil, Iran
3- Research Laboratory of Embryology and Stem Cells, Department of Anatomical Sciences, Faculty of Medicine, Ardabil University of Medical Sciences, Ardabil, Iran.
2- Faculty of Medicine, Ardabil University of Medical Sciences, Ardabil, Iran
3- Research Laboratory of Embryology and Stem Cells, Department of Anatomical Sciences, Faculty of Medicine, Ardabil University of Medical Sciences, Ardabil, Iran.
Abstract: (1353 Views)
Background and Aim: Identifying and demarcating the masses and diagnosing the disease in breast tissue is a serious challenge in diagnosing this cancer. Mammography is currently the most common method to diagnose breast cancer, in which incorrectly identifying the masses can lead to misdiagnosis or sampling of breast tissue. In this study, using feature extraction in medical image processing, we tried to make a diagnosis with better accuracy than in the past.
Materials and Methods: Mammographic image features were extracted using the Harris feature extraction algorithm. Mammographic images were analyzed using Matlab2019a software and ideal outputs were obtained.
Findings: Mammographic images were pre-processed and Harris algorithm was applied. In the output of the proposed algorithm, the accuracy and speed of detection of the algorithm were higher in comparison to other routine methods.
Conclusion: The purpose of extracting the Harris property is to make the raw data more usable for future statistical processing. it is expected that in the future, feature extraction will be more accurate, and more details will be provided to the machine vision systems to identify objects in the image.
Materials and Methods: Mammographic image features were extracted using the Harris feature extraction algorithm. Mammographic images were analyzed using Matlab2019a software and ideal outputs were obtained.
Findings: Mammographic images were pre-processed and Harris algorithm was applied. In the output of the proposed algorithm, the accuracy and speed of detection of the algorithm were higher in comparison to other routine methods.
Conclusion: The purpose of extracting the Harris property is to make the raw data more usable for future statistical processing. it is expected that in the future, feature extraction will be more accurate, and more details will be provided to the machine vision systems to identify objects in the image.
Type of Study: Research |
Subject:
Special
Received: 2022/10/24 | Accepted: 2022/11/01 | Published: 2022/11/01
Received: 2022/10/24 | Accepted: 2022/11/01 | Published: 2022/11/01
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