Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/5597
Title: Support Vector Machine Based Texture Feature Extraction Technique for Classification of Breast Cancer From Ultrasound Images
Authors: Sharma, Shreya
Jain, Shruti [Guided by]
Keywords: Breast cancers
Ultrasound images
MATLAB
Support vector machine
Issue Date: 2017
Publisher: Jaypee University of Information Technology, Solan, H.P.
Abstract: Breast Cancers is such a ailment that has got excellent attention within many years. In breast cancer the breast lesion are differentiated into two instructions i.e. Benign and Malignant. Computer-Aided Detection (CAD) system is designed to resource radiologists in detecting lesions which could imply the presence of breast cancers. The ROI is extracted from the ultrasonic photos, the usage of imageJ software after which the unique photograph processing techniques are carried out i.e. preprocessing, feature extraction and feature classification using MATLAB. SVM classifier is significantly used for category. Classification of breast ultrasound images using Statistical and Transform domain feature extraction techniques were data is partitioned by hold-out method and classified using Support Vector Machine (SVM) classifier. SVM trains a model that assigns unseen new objects into a specific category. The best obtained result out of all the features used is calculated using Fourier Power Spectrum (FPS) feature.
URI: http://ir.juit.ac.in:8080/jspui//xmlui/handle/123456789/5597
Appears in Collections:Dissertations (M.Tech.)



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