Classification algorithms for microcalcifications in mammograms (Review)
نویسندگان
چکیده
منابع مشابه
Wavelet Based Microcalcifications Detection in Digitized Mammograms
Detection of microcalcifications in mammograms has received much attention from researchers and public health practitioners in these last years. The challenge is to quickly and accurately overcome the development of breast cancer which affects more and more women through the world. Microcalcifications appear in a mammogram as fine, granular clusters, which are often difficult to identify in a r...
متن کاملSegmentation and feature extraction for reliable classification of microcalcifications in digital mammograms
Microcalcifications are one of more important signs enabling detection of breast cancer at an early stage. The main goal of the research was designing and realization of a system for automatic detection and classification of microcalcifications, taking advantage of the proposed automatic feature selection algorithm. The first step of the detection algorithm is to segment the individual objects:...
متن کاملFuzzy technique for microcalcifications clustering in digital mammograms
BACKGROUND Mammography has established itself as the most efficient technique for the identification of the pathological breast lesions. Among the various types of lesions, microcalcifications are the most difficult to identify since they are quite small (0.1-1.0 mm) and often poorly contrasted against an images background. Within this context, the Computer Aided Detection (CAD) systems could t...
متن کاملAnt Colony Optimization and a New Particle Swarm Optimization algorithm for Classification of Microcalcifications in Mammograms
Genetic Algorithm (GA), Ant Colony Optimization (ACO) algorithm and Particle Swarm Optimization (PSO) are proposed for feature selection, and their performance is compared. The Spatial Gray Level Dependence Method (SGLDM) is used for feature extraction. The selected features are fed to a three-layer Backpropagation Network hybrid with Ant Colony Optimization and Particle Swarm Optimization (BPN...
متن کاملSupport vector machine learning for detection of microcalcifications in mammograms
Microcalcification (MC) clusters in mammograms can be an indicator of breast cancer. In this work we propose for the first time the use of support vector machine (SVM) learning for automated detection of MCs in digitized mammograms. In the proposed framework, MC detection is formulated as a supervised-learning problem and the method of SVM is employed to develop the detection algorithm. The pro...
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ژورنال
عنوان ژورنال: Oncology Reports
سال: 2006
ISSN: 1021-335X,1791-2431
DOI: 10.3892/or.15.4.1049