شماره ركورد كنفرانس :
3297
عنوان مقاله :
Breast cancer detection without removal pectoral muscle by extraction turn counts feature
عنوان به زبان ديگر :
Breast cancer detection without removal pectoral muscle by extraction turn counts feature
پديدآورندگان :
Kharaji Nezhadian Farzam Faculty of Biomedical Engineering Islamic Azad University - Science and Research branch Tehran - Iran , Rashidi Saeid Faculty of Biomedical Engineering Islamic Azad University - Science and Research branch Tehran - Iran
كليدواژه :
Classification , Turn count , Mammogram , Breast cancer
عنوان كنفرانس :
نوزدهمين سمپوزيوم بين المللي هوش مصنوعي و پردازش سيگنال
چكيده لاتين :
Abstract—During late decade breast cancer is recognized as
major cause of death among women and the number of breast
cancer patients is increasing. There is more evidence that women
in 15-54 years old are died by breast cancer. Breast cancer
cannot be prevented because its major factors have not been
identified. Therefore earlier diagnosis can increase the possibility
of improvement. The aim of this study was to extract the feature
without removing pectoral muscle in preprocessing stage using a
new and efficient method. Database of MIAS mammography
images was used to classify normal/ abnormal individuals and
benign/ malignant cancer patients and the results of support
vector machine classifier showed accuracy of 95.80 and 86.50
respectively.