Feature Extraction Techniques for Mass Detection in Digital Mammogram (Review)

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dc.contributor.authorAdeyemo, Temitope Tosin
dc.contributor.authorAdepoju, Temilola Morufat
dc.contributor.authorSobowale, Adedayo Aladejobi
dc.contributor.authorOyediran, Mayowa Oyedepo
dc.contributor.authorOmidiora, Elijah Olusayo
dc.contributor.authorOlabiyisi, Stephen Olatude
dc.date.accessioned2023-12-04T14:13:50Z
dc.date.available2023-12-04T14:13:50Z
dc.date.issued2017-12-08
dc.description.abstractOne of the most common diseases in women today is breast cancer. The method of detection and analyzing breast images according to literature, to mention few are mammography, magnetic resonance, thermography and ultrasound of which mammography is the most accurate and low cost method. Mass is a major symptom of breast abnormality. Despite the high success of mammography in mass detection, radiologists find it difficult to interpret breast abnormality and take decision. Computer Aided Detection (CADe) and Computer Aided Diagnosis (CADx) are the two systems to improve radiologists’ accuracy of detection and, classification of breast cancer into benign or malignant prior to biopsy. However, the optimal classification rate of CAD system depends on effectiveness of feature extraction technique. This paper present review of different feature extraction Techniques (FETs) that have been adopted for mass detection and classification.en_US
dc.identifier.urihttp://repository.acu.edu.ng:8080/jspui/handle/123456789/355
dc.language.isoenen_US
dc.publisherJournal of Scientific Research & Reportsen_US
dc.subjectCanceren_US
dc.subjectfeature extractionen_US
dc.subjectbreasten_US
dc.subjectmammogramen_US
dc.subjectmassen_US
dc.subjectregion of interesten_US
dc.subjectbenignen_US
dc.subjectmalignanten_US
dc.titleFeature Extraction Techniques for Mass Detection in Digital Mammogram (Review)en_US
dc.typeArticleen_US

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