A Review on Feature Selection Techniques in Digital Mammograms

The most of the women in the world are suffering from a deadly disease called Breast Cancer (BC). Breast cancer is analyzed by using imaging modalities such as mammograms, magnetic resonance imaging, ultrasound, and thermograms. Among all, mammograms are the low dosage, less cost, more effective, an...

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Bibliographic Details
Published in:Turkish journal of computer and mathematics education 2021-04, Vol.12 (2), p.3329-3338
Main Authors: Kumara, L Kanya, Jagadesh, B N
Format: Article
Language:English
Subjects:
Breast cancer
Classifiers
Magnetic resonance imaging
Mammography
Medical imaging
Optimization
Optimization techniques
Physicians
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Summary:The most of the women in the world are suffering from a deadly disease called Breast Cancer (BC). Breast cancer is analyzed by using imaging modalities such as mammograms, magnetic resonance imaging, ultrasound, and thermograms. Among all, mammograms are the low dosage, less cost, more effective, and accurate method to detect BC in early stages. There are many Computer-Aided Detection (CAD) systems for the automatic detection of masses in mammograms. These techniques are helping radiologists and physicians in diagnosing disease. The objective of this paper is to overview different CAD systems in which mainly we focused on feature selection, as feature selection techniques are used to reduce the complexity of the classifiers and also increase the accuracy. We conclude that suitable optimization techniques should be chosen to increase the accuracy of the classifier so that we can increase the survival rate of the patient.
ISSN:1309-4653
1309-4653
DOI:10.17762/turcomat.v12i2.2392