منابع مشابه
Efficient Classification of Cancerous Masses in Mammogram
Breast cancer is one of the most common forms of cancer in women. In order to reduce the death rate , early detection of cancerous regions in mammogram images is needed. The existing system is not so accurate and it is time consuming. The Proposed system is mainly used for automatic segmentation of the mammogram images and classifies them as benign, malignant or normal based on the decision tre...
متن کاملMammogram Classification Using Association Rule Mining
Breast cancer is the primary and the most common disease found among women. It is responsible for rapid growth in mortality rate among all types of cancers in women. Today, mammography the most powerful screening technique is used for early detection of cancer which increases the chance of successful treatment. Screening with mammography can show changes in the breast up to 2-3years before a ph...
متن کاملFuzzy Soft Set based Classification for Mammogram Images
Mammogram images classification using data mining methods review on past literature showed that these methods are relatively successful however accuracy and efficiency are still outstanding issues. Therefore, the positive reviews produced from past works on fuzzy soft set based classification have resulted in an attempt to use similarity approach on fuzzy soft set for mammogram images classific...
متن کاملA New Approach for Mammogram Image Classification Using Fractal Properties
Accurate classification of images is essential for the analysis of mammograms in computer aided diagnosis of breast cancer. We propose a new approach to classify mammogram images based on fractal features. Given a mammogram image, we first eliminate all the artifacts and extract the salient features such as Fractal Dimension (FD) and Fractal Signature (FS). These features provide good descripti...
متن کاملRough Set Approach for Classification of Breast Cancer Mammogram Images
Breast cancer represents the second leading cause of cancer deaths in women today and it is the most common type of cancer in women. This paper presents an efficient classification algorithm in digital mammograms in the context of rough set theory. Feature extractions acquired in this work are derived from the gray-level co-occurrence matrix. The features are extracted, normalized and then the ...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2016
ISSN: 0975-8887
DOI: 10.5120/ijca2016911681