Computerized Analysis of Mammographic Images for Detection and Characterization of Breast Cancer

Computerized Analysis of Mammographic Images for Detection and Characterization of Breast Cancer

Author: Paola Casti

Publisher: Morgan & Claypool Publishers

ISBN: 9781681731575

Category: Technology & Engineering

Page: 186

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The identification and interpretation of the signs of breast cancer in mammographic images from screening programs can be very difficult due to the subtle and diversified appearance of breast disease. This book presents new image processing and pattern recognition techniques for computer-aided detection and diagnosis of breast cancer in its various forms. The main goals are: (1) the identification of bilateral asymmetry as an early sign of breast disease which is not detectable by other existing approaches; and (2) the detection and classification of masses and regions of architectural distortion, as benign lesions or malignant tumors, in a unified framework that does not require accurate extraction of the contours of the lesions. The innovative aspects of the work include the design and validation of landmarking algorithms, automatic Tabár masking procedures, and various feature descriptors for quantification of similarity and for contour independent classification of mammographic lesions. Characterization of breast tissue patterns is achieved by means of multidirectional Gabor filters. For the classification tasks, pattern recognition strategies, including Fisher linear discriminant analysis, Bayesian classifiers, support vector machines, and neural networks are applied using automatic selection of features and cross-validation techniques. Computer-aided detection of bilateral asymmetry resulted in accuracy up to 0.94, with sensitivity and specificity of 1 and 0.88, respectively. Computer-aided diagnosis of automatically detected lesions provided sensitivity of detection of malignant tumors in the range of [0.70, 0.81] at a range of falsely detected tumors of [0.82, 3.47] per image. The techniques presented in this work are effective in detecting and characterizing various mammographic signs of breast disease.
Mammographic Image Analysis
Language: en
Pages: 379
Authors: R. Highnam, J.M. Brady
Categories: Medical
Type: BOOK - Published: 2012-12-06 - Publisher: Springer Science & Business Media

Breast cancer is a major health problem in the Western world, where it is the most common cancer among women. Approximately 1 in 12 women will develop breast cancer during the course of their lives. Over the past twenty years there have been a series of major advances in the
Computerized Analysis of Mammographic Images for Detection and Characterization of Breast Cancer
Language: en
Pages: 186
Authors: Paola Casti, Arianna Mencattini, Marcello Salmeri, Rangaraj M. Rangayyan
Categories: Technology & Engineering
Type: BOOK - Published: 2017-07-06 - Publisher: Morgan & Claypool Publishers

The identification and interpretation of the signs of breast cancer in mammographic images from screening programs can be very difficult due to the subtle and diversified appearance of breast disease. This book presents new image processing and pattern recognition techniques for computer-aided detection and diagnosis of breast cancer in its
State of the Art in Digital Mammographic Image Analysis
Language: en
Pages: 291
Authors: K. W. Bowyer, S. Astley
Categories: Medical
Type: BOOK - Published: 1994 - Publisher: World Scientific

This book provides a detailed assessment of the state of the art in automated techniques for the analysis of digital mammogram images. Topics covered include a variety of approaches for image processing and pattern recognition aimed at assisting the physician in the task of detecting tumors from evidence in mammogram
Advances in Artificial Intelligence and Its Applications
Language: en
Pages: 585
Authors: Félix Castro, Alexander Gelbukh, Miguel González Mendoza
Categories: Computers
Type: BOOK - Published: 2013-11-22 - Publisher: Springer

The two-volume set LNAI 8265 and LNAI 8266 constitutes the proceedings of the 12th Mexican International Conference on Artificial Intelligence, MICAI 2013, held in Mexico City, Mexico, in November 2013. The total of 85 papers presented in these proceedings were carefully reviewed and selected from 284 submissions. The first volume
Practical Digital Mammography
Language: en
Pages: 224
Authors: Beverly Hashimoto
Categories: Medical
Type: BOOK - Published: 2011-01-01 - Publisher: Thieme

Practical Digital Mammography provides breast imagers with a systematic, problem-solving approach to detecting and assessing the most subtle signs of breast cancer malignancies. The book opens with concise coverage of the fundamentals, including physics, equipment, and normal anatomy. Separate chapters provide straightforward descriptions and clear illustrations of the digital mammographic