Fractal analysis of breast masses in mammograms /

Bibliographic Details
Main Author:	Cabral, Thanh M. (Thanh Minh)
Other Authors:	Rangayyan, Rangaraj M.
Format:	eBook
Language:	English
Published:	San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, [2012]
Series:	Synthesis lectures on biomedical engineering ; #46.
Subjects:	Breast > Radiography. Radiography, Medical > Digital techniques. Fractals. Mammography. Radiographic Image Interpretation, Computer-Assisted. HEALTH & FITNESS / Women's Health. MEDICAL / Reproductive Medicine & Technology. blanket method box-counting method breast cancer breast masses compactness computer-aided diagnosis digital image processing Fourier descriptors fractal analysis fractal dimension fractional concavity mammography pattern classification pattern recognition power spectral analysis ruler method shape analysis signature of a contour spiculation index texture analysis Electronic books.
Online Access:	Connect to the full text of this electronic book

Description
Abstract:	Fractal analysis is useful in digital image processing for the characterization of shape roughness and gray-scale texture or complexity. Breast masses present shape and gray-scale characteristics in mammograms that vary between benign masses and malignant tumors. This book demonstrates the use of fractal analysis to classify breast masses as benign masses or malignant tumors based on the irregularity exhibited in their contours and the gray-scale variability exhibited in their mammographic images. A few different approaches are described to estimate the fractal dimension (FD) of the contour of a mass, including the ruler method, box-counting method, and the power spectral analysis (PSA) method. Procedures are also described for the estimation of the FD of the gray-scale image of a mass using the blanket method and the PSA method.
Item Description:	Part of: Synthesis digital library of engineering and computer science. Series from website. Electronic resource.
Physical Description:	1 online resource (xx, 98 pages) : illustrations
Bibliography:	Includes bibliographical references (pages 87-96).
ISBN:	9781627050692 (electronic bk.) 1627050698 (electronic bk.)
ISSN:	1930-0336 ;