An enhancement of multi classifiers voting method for mammogram image based on image histogram equalization

Breast cancer is one the most curable cancer types if it can be diagnosed early. Research efforts have reported with increasing confirmation that the computation methods have greater accurate diagnosis ability. An enhancement of multi classifiers voting technique based on histogram equalization as a...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Ibrahim, Ashraf Osman, Ahmed, Ali, Azizah, Anik Hanifatul, Lashar, Saima Anwar, Alobeed, Mohamed Alhaj, Kasim, Shahreen, Ismail, Mohd Arfian
التنسيق: مقال
اللغة:English
منشور في: Penerbit UTHM 2018
الموضوعات:
الوصول للمادة أونلاين:http://eprints.uthm.edu.my/3661/1/AJ%202018%20%28712%29%20An%20enhancement%20of%20multi%20classifiers%20voting%20method%20for%20mammogram%20image%20based%20on%20image%20histogram%20equalization.pdf
http://eprints.uthm.edu.my/3661/
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الوصف
الملخص:Breast cancer is one the most curable cancer types if it can be diagnosed early. Research efforts have reported with increasing confirmation that the computation methods have greater accurate diagnosis ability. An enhancement of multi classifiers voting technique based on histogram equalization as a preprocessing stage proposed in this paper. The methodology is based on five phases starting by mammogram images collection, preprocessing (histogram equalization and image cropping based region of interest (ROI)), features extracting, classification and last evaluating the classification results. An experimental conducted on different training-testing partitions of the dataset. The numerical results demonstrate that the proposed scheme achieves an accuracy rate of 81.25% and outperformed the accuracy of voting method without using histogram equalization.