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Fractal Analysis of Breast Masses in Mammograms (Paperback)
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Fractal Analysis of Breast Masses in Mammograms (Paperback)
Series: Synthesis Lectures on Biomedical Engineering
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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. To facilitate comparative analysis of FD as a feature
for pattern classification of breast masses, several other shape
features and texture measures are described in the book. The shape
features described include compactness, spiculation index,
fractional concavity, and Fourier factor. The texture measures
described are statistical measures derived from the gray-level
cooccurrence matrix of the given image. Texture measures reveal
properties about the spatial distribution of the gray levels in the
given image; therefore, the performance of texture measures may be
dependent on the resolution of the image. For this reason, an
analysis of the effect of spatial resolution or pixel size on
texture measures in the classification of breast masses is
presented in the book. The results demonstrated in the book
indicate that fractal analysis is more suitable for
characterization of the shape than the gray-level variations of
breast masses, with area under the receiver operating
characteristics of up to 0.93 with a dataset of 111 mammographic
images of masses. The methods and results presented in the book are
useful for computer-aided diagnosis of breast cancer. Table of
Contents: Computer-Aided Diagnosis of Breast Cancer / Detection and
Analysis of\newline Breast Masses / Datasets of Images of Breast
Masses / Methods for Fractal Analysis / Pattern Classification /
Results of Classification of Breast Masses / Concluding Remarks
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