Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.

Part of: Synthesis digital library of engineering and computer science.

Series from website.

Includes bibliographical references (p. 87-96).

Preface -- Acknowledgments -- List of symbols and abbreviations --

1. Computer-aided diagnosis of breast cancer -- 1.1 Mammography -- 1.2 Computer-aided diagnosis of breast cancer -- 1.3 Objectives and organization of the book --

2. Detection and analysis of breast masses -- 2.1 Characteristics of breast masses -- 2.2 Review of methods for CAD of breast masses -- 2.3 Review of methods for analysis of breast masses -- 2.3.1 Representation of breast masses for shape and texture analysis -- 2.3.2 Shape analysis of breast masses -- 2.3.3 Texture analysis of breast masses -- 2.4 Remarks --

[3]. Datasets of images of breast masses --

4. Methods for fractal analysis -- 4.1 Fractals -- 4.1.1 Famous fractals -- 4.1.2 Fractals in biology -- 4.1.3 Fractal dimension -- 4.1.4 Applications of fractal analysis -- 4.2 Fractal analysis of shape -- 4.2.1 The ruler method -- 4.2.2 The box-counting method -- 4.2.3 The power spectral analysis method -- 4.2.4 Evaluation of the methods with test patterns -- 4.3 Fractal analysis of gray-level images -- 4.3.1 The blanket method -- 4.3.2 Power spectral analysis of gray-level images -- 4.3.3 Evaluation of the methods with test images -- 4.4 Remarks --

5. Pattern classification -- 5.1 Fisher linear discriminant analysis -- 5.2 The Bayesian classifier -- 5.3 Receiver operating characteristics -- 5.4 The t-test and p-value -- 5.5 Remarks --

6. Results of classification of breast masses -- 6.1 Rank-ordering contours of masses by fractal dimension -- 6.2 Results of shape analysis -- 6.2.1 Classification of breast masses using fractal dimension -- 6.2.2 Comparative analysis of shape factors -- 6.3 Results of analysis of gray-scale variation -- 6.3.1 Fractal analysis of gray-scale variation -- 6.3.2 Haralick's texture measures -- 6.4 Discussion --

7. Concluding remarks -- References -- Authors' biographies.

Abstract freely available; full-text restricted to subscribers or individual document purchasers.

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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.

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Title from PDF t.p. (viewed on November 20, 2012).