Hybrid methods for feature extraction for breast masses classification
نویسندگان
چکیده
منابع مشابه
Feature Extraction and Classification of Mammographic Masses
The aim of this project is to classify the mammographic masses as benign or malignant using texture and shape features. A set of 73 mammograms is used for the analysis, out of which 41 are benign and 32 are malignant. Manually segmented masses are obtained from the DDSM, USF database [2]. Texture and shape features are extracted from the manually segmented masses. Stepwise linear discriminant a...
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Content Based Image Retrieval is a technique which uses visual contents for searching images from large scale image databases Information extracted from images such as color, texture and shape are known as feature vectors. Using multiple feature vectors to describe an image during retrieval process increases the accuracy when compared to the retrieval using single feature vector. The objective ...
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This paper presents an evaluation and comparison of the performance of three different feature extraction methods for classification of normal and abnormal patterns in mammogram. Three different feature extraction methods used here are intensity histogram, GLCM (Grey Level Co-occurrence Matrix) and intensity based features. A supervised classifier system based on neural network is used. The per...
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ژورنال
عنوان ژورنال: Egyptian Informatics Journal
سال: 2018
ISSN: 1110-8665
DOI: 10.1016/j.eij.2017.08.001