Characterization of Breast Tissues using Texture Analysis


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  • Product Description

The identification of normal breast tissues in mammograms is an important step in identifying abnormal tissues, or masses. The major focus of this study is to use image-processing techniques to characterize the normal breast tissues. Clustering techniques have been developed to classify the breast tissue into one of 5 different tissue types including fat, glandular, connective, dense tissues and pectoral muscle. The classification was achieved by using a novel technique (dSGLD) involving a subset of the elements (the values on the diagonals) in the Spatial Grey Level Dependence (SGLD) matrix which was calculated using texture features. The ultimate goal of this study is therefore to design and implement a computerized characterization method that mimics the radiologist’s characterization of tissue composition in digitized mammograms. The classification results using dSGLD and SGLD features achieved an acceptable accuracy.

Product Specifications
SKU :COC95377
AuthorMohamed Gar-elnabi,Michael Alport and William Rae
Number of Pages180
Publishing Year2011-09-29T00:00:00.000
Edition1 st
Book TypeMusic
Country of ManufactureIndia
Product BrandLAP LAMBERT Academic Publishing
Product Packaging InfoBox
In The Box1 Piece
Product First Available On ClickOnCare.com2015-08-14 00:00:00
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