Computerized Analysis Of Mammographic Images For Detection And Characterization Of Breast Cancer

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

Arianna Mencattini,Paola Casti
Computerized Analysis of Mammographic Images for Detection and Characterization of Breast Cancer Book PDF

Author : Arianna Mencattini,Paola Casti
Publisher : Springer Nature
Page : 166 pages
File Size : 48,8 Mb
Release : 2022-05-31
Category : Technology & Engineering
ISBN : 9783031016646

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Computerized Analysis of Mammographic Images for Detection and Characterization of Breast Cancer by Arianna Mencattini,Paola Casti Pdf

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.

Computer-aided Detection of Architectural Distortion in Prior Mammograms of Interval Cancer

Shantanu Banik,Rangaraj Rangayyan,J.E. Leo Desautels
Computer aided Detection of Architectural Distortion in Prior Mammograms of Interval Cancer Book PDF

Author : Shantanu Banik,Rangaraj Rangayyan,J.E. Leo Desautels
Publisher : Morgan & Claypool Publishers
Page : 195 pages
File Size : 53,9 Mb
Release : 2013-01-01
Category : Technology & Engineering
ISBN : 9781627050838

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Computer-aided Detection of Architectural Distortion in Prior Mammograms of Interval Cancer by Shantanu Banik,Rangaraj Rangayyan,J.E. Leo Desautels Pdf

Architectural distortion is an important and early sign of breast cancer, but because of its subtlety, it is a common cause of false-negative findings on screening mammograms. Screening mammograms obtained prior to the detection of cancer could contain subtle signs of early stages of breast cancer, in particular, architectural distortion. This book presents image processing and pattern recognition techniques to detect architectural distortion in prior mammograms of interval-cancer cases. The methods are based upon Gabor filters, phase portrait analysis, procedures for the analysis of the angular spread of power, fractal analysis, Laws' texture energy measures derived from geometrically transformed regions of interest (ROIs), and Haralick's texture features. With Gabor filters and phase-portrait analysis, 4,224 ROIs were automatically obtained from 106 prior mammograms of 56 interval-cancer cases, including 301 true-positive ROIs related to architectural distortion, and from 52 mammograms of 13 normal cases. For each ROI, the fractal dimension, the entropy of the angular spread of power, 10 Laws' texture energy measures, and Haralick's 14 texture features were computed. The areas under the receiver operating characteristic (ROC) curves obtained using the features selected by stepwise logistic regression and the leave-one-image-out method are 0.77 with the Bayesian classifier, 0.76 with Fisher linear discriminant analysis, and 0.79 with a neural network classifier. Free-response ROC analysis indicated sensitivities of 0.80 and 0.90 at 5.7 and 8.8 false positives (FPs) per image, respectively, with the Bayesian classifier and the leave-one-image-out method. The present study has demonstrated the ability to detect early signs of breast cancer 15 months ahead of the time of clinical diagnosis, on the average, for interval-cancer cases, with a sensitivity of 0.8 at 5.7 FP/image. The presented computer-aided detection techniques, dedicated to accurate detection and localization of architectural distortion, could lead to efficient detection of early and subtle signs of breast cancer at pre-mass-formation stages. Table of Contents: Introduction / Detection of Early Signs of Breast Cancer / Detection and Analysis of Oriented Patterns / Detection of Potential Sites of Architectural Distortion / Experimental Set Up and Datasets / Feature Selection and Pattern Classification / Analysis of Oriented Patterns Related to Architectural Distortion / Detection of Architectural Distortion in Prior Mammograms / Concluding Remarks

State of the Art in Digital Mammographic Image Analysis

K. W. Bowyer,S. Astley
State of the Art in Digital Mammographic Image Analysis Book PDF

Author : K. W. Bowyer,S. Astley
Publisher : World Scientific
Page : 312 pages
File Size : 54,9 Mb
Release : 1994
Category : Medical
ISBN : 9810215096

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State of the Art in Digital Mammographic Image Analysis by K. W. Bowyer,S. Astley Pdf

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 images. The chapters are written by recognized experts in the field and are revised versions of papers selected from those presented at the “First International Workshop on Mammogram Image Analysis” held in San Jose as part of the 1993 Biomedical Image Processing conference.

Fractal Analysis of Breast Masses in Mammograms

Thanh M. Cabral,Rangaraj Rangayyan
Fractal Analysis of Breast Masses in Mammograms Book PDF

Author : Thanh M. Cabral,Rangaraj Rangayyan
Publisher : Morgan & Claypool Publishers
Page : 120 pages
File Size : 53,5 Mb
Release : 2012-10-01
Category : Technology & Engineering
ISBN : 9781627050692

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Fractal Analysis of Breast Masses in Mammograms by Thanh M. Cabral,Rangaraj Rangayyan Pdf

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

Mammography and Beyond

National Research Council,Commission on Life Sciences,Institute of Medicine,National Cancer Policy Board,Committee on the Early Detection of Breast Cancer
Mammography and Beyond Book PDF

Author : National Research Council,Commission on Life Sciences,Institute of Medicine,National Cancer Policy Board,Committee on the Early Detection of Breast Cancer
Publisher : National Academies Press
Page : 34 pages
File Size : 54,9 Mb
Release : 2001-06-04
Category : Medical
ISBN : 9780309075503

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Mammography and Beyond by National Research Council,Commission on Life Sciences,Institute of Medicine,National Cancer Policy Board,Committee on the Early Detection of Breast Cancer Pdf

X-ray mammography screening is the current mainstay for early breast cancer detection. It has been proven to detect breast cancer at an earlier stage and to reduce the number of women dying from the disease. However, it has a number of limitations. These current limitations in early breast cancer detection technology are driving a surge of new technological developments, from modifications of x-ray mammography such as computer programs that can indicate suspicious areas, to newer methods of detection such as magnetic resonance imaging (MRI) or biochemical tests on breast fluids. To explore the merits and drawbacks of these new breast cancer detection techniques, the Institute of Medicine of the National Academy of Sciences convened a committee of experts. During its year of operation, the committee examined the peer-reviewed literature, consulted with other experts in the field, and held two public workshops. In addition to identifying promising new technologies for early detection, the committee explored potential barriers that might prevent the development of new detection methods and their common usage. Such barriers could include lack of funding from agencies that support research and lack of investment in the commercial sector; complicated, inconsistent, or unpredictable federal regulations; inadequate insurance reimbursement; and limited access to or unacceptability of breast cancer detection technology for women and their doctors. Based on the findings of their study, the committee prepared a report entitled Mammography and Beyond: Developing Technology for Early Detection of Breast Cancer, which was published in the spring of 2001. This is a non-technical summary of that report.

Digital Mammography

Nico Karssemeijer,Martin Thijssen,Jan Hendriks,Leon van Erning
Digital Mammography Book PDF

Author : Nico Karssemeijer,Martin Thijssen,Jan Hendriks,Leon van Erning
Publisher : Springer Science & Business Media
Page : 520 pages
File Size : 53,5 Mb
Release : 2012-12-06
Category : Medical
ISBN : 9789401153188

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Digital Mammography by Nico Karssemeijer,Martin Thijssen,Jan Hendriks,Leon van Erning Pdf

In June 1998 the Fourth International Workshop on Digital Mammography was held in Nijmegen, The Netherlands, where it was hosted by the department of Radiology of the University Hospital Nijmegen. This series of meetings was initiated at the 1993 SPIE Biomedical Image Processing Conference in San Jose, USA, where a number of sessions were entirely devoted to mammographic image analysis. At very successful subsequent workshops held in York, UK (1994) and Chicago, USA (1996), the scope of the conference was broadened, establishing a platform for presentation and discussion of new developments in digital mammog raphy. Topics that are addressed at these meetings are computer-aided diagnosis, image processing, detector development, system design, observer performance and clinical evaluation. The goal is to bring researchers from universities, breast cancer experts, and engineers together, to exchange information and present new scientific developments in this rapidly evolving field. This book contains all the scientific papers and posters presented at the work shop in Nijmegen. Contributions came from as many as 20 different countries and 190 participants attended the meeting. At a technical exhibit companies demon strated new products and work in progress. Abstracts of all papers were reviewed by members of the scientific committee. Many of the accepted papers had excellent quality, but due to limited space not all of them could be included as full papers in these proceedings. Papers that were rated high by the reviewers are included as long or short papers, others appear as extended abstracts in the last chapter.

Fractal Analysis of Breast Masses in Mammograms

Thanh Cabral,Rangaraj Rangayyan
Fractal Analysis of Breast Masses in Mammograms Book PDF

Author : Thanh Cabral,Rangaraj Rangayyan
Publisher : Springer Nature
Page : 104 pages
File Size : 46,5 Mb
Release : 2022-06-01
Category : Technology & Engineering
ISBN : 9783031016547

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Fractal Analysis of Breast Masses in Mammograms by Thanh Cabral,Rangaraj Rangayyan Pdf

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

Mammographic Image Analysis

R. Highnam,J.M. Brady
Mammographic Image Analysis Book PDF

Author : R. Highnam,J.M. Brady
Publisher : Springer Science & Business Media
Page : 383 pages
File Size : 55,7 Mb
Release : 2012-12-06
Category : Medical
ISBN : 9789401146135

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Mammographic Image Analysis by R. Highnam,J.M. Brady Pdf

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 manage ment of women with breast cancer, ranging from novel chemotherapy and radiotherapy treatments to conservative surgery. The next twenty years are likely to see computerized image analysis playing an increasingly important role in patient management. As applications of image analysis go, medical applications are tough in general, and breast cancer image analysis is one of the toughest. There are many reasons for this: highly variable and irregular shapes of the objects of interest, changing imaging conditions, and the densely textured nature of the images. Add to this the increasing need for quantitative informa tion, precision, and reliability (very few false positives), and the image pro cessing challenge becomes quite daunting, in fact it pushes image analysis techniques right to their limits.

Mammography and Beyond

National Research Council,Division on Earth and Life Studies,Institute of Medicine,National Cancer Policy Board,Committee on Technologies for the Early Detection of Breast Cancer
Mammography and Beyond Book PDF

Author : National Research Council,Division on Earth and Life Studies,Institute of Medicine,National Cancer Policy Board,Committee on Technologies for the Early Detection of Breast Cancer
Publisher : National Academies Press
Page : 312 pages
File Size : 45,8 Mb
Release : 2001-07-23
Category : Medical
ISBN : 0309171318

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Mammography and Beyond by National Research Council,Division on Earth and Life Studies,Institute of Medicine,National Cancer Policy Board,Committee on Technologies for the Early Detection of Breast Cancer Pdf

Each year more than 180,000 new cases of breast cancer are diagnosed in women in the U.S. If cancer is detected when small and local, treatment options are less dangerous, intrusive, and costly-and more likely to lead to a cure. Yet those simple facts belie the complexity of developing and disseminating acceptable techniques for breast cancer diagnosis. Even the most exciting new technologies remain clouded with uncertainty. Mammography and Beyond provides a comprehensive and up-to-date perspective on the state of breast cancer screening and diagnosis and recommends steps for developing the most reliable breast cancer detection methods possible. This book reviews the dramatic expansion of breast cancer awareness and screening, examining the capabilities and limitations of current and emerging technologies for breast cancer detection and their effectiveness at actually reducing deaths. The committee discusses issues including national policy toward breast cancer detection, roles of public and private agencies, problems in determining the success of a technique, availability of detection methods to specific populations of women, women's experience during the detection process, cost-benefit analyses, and more. Examining current practices and specifying research and other needs, Mammography and Beyond will be an indispensable resource to policy makers, public health officials, medical practitioners, researchers, women's health advocates, and concerned women and their families.

Recent Advances in Breast Imaging, Mammography, and Computer-aided Diagnosis of Breast Cancer

Jasjit S. Suri,Rangaraj M. Rangayyan
Recent Advances in Breast Imaging Mammography and Computer aided Diagnosis of Breast Cancer Book PDF

Author : Jasjit S. Suri,Rangaraj M. Rangayyan
Publisher : CCH
Page : 1012 pages
File Size : 50,5 Mb
Release : 2006
Category : Breast
ISBN : 0819460818

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Recent Advances in Breast Imaging, Mammography, and Computer-aided Diagnosis of Breast Cancer by Jasjit S. Suri,Rangaraj M. Rangayyan Pdf

Breast cancer is the most common type of cancer found in women worldwide; approximately 10 per cent of women are confronted with breast cancer in their lives. Breast cancer can be most efficiently treated if detected at an early stage. This book focuses primarily on the application of computer vision for early lesion identification in mammograms and breast-imaging volumes through computer-aided diagnostics (CAD). Colour illustrations are included in the text, and an accompanying CD-ROM contains other full-colour images.

Modeling and Analysis of Shape with Applications in Computer-aided Diagnosis of Breast Cancer

Denise Guliato,Rangaraj Rangayyan
Modeling and Analysis of Shape with Applications in Computer aided Diagnosis of Breast Cancer Book PDF

Author : Denise Guliato,Rangaraj Rangayyan
Publisher : Springer Nature
Page : 75 pages
File Size : 49,5 Mb
Release : 2022-05-31
Category : Technology & Engineering
ISBN : 9783031794292

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Modeling and Analysis of Shape with Applications in Computer-aided Diagnosis of Breast Cancer by Denise Guliato,Rangaraj Rangayyan Pdf

Malignant tumors due to breast cancer and masses due to benign disease appear in mammograms with different shape characteristics: the former usually have rough, spiculated, or microlobulated contours, whereas the latter commonly have smooth, round, oval, or macrolobulated contours. Features that characterize shape roughness and complexity can assist in distinguishing between malignant tumors and benign masses. In spite of the established importance of shape factors in the analysis of breast tumors and masses, difficulties exist in obtaining accurate and artifact-free boundaries of the related regions from mammograms. Whereas manually drawn contours could contain artifacts related to hand tremor and are subject to intra-observer and inter-observer variations, automatically detected contours could contain noise and inaccuracies due to limitations or errors in the procedures for the detection and segmentation of the related regions. Modeling procedures are desired to eliminate the artifacts in a given contour, while preserving the important and significant details present in the contour. This book presents polygonal modeling methods that reduce the influence of noise and artifacts while preserving the diagnostically relevant features, in particular the spicules and lobulations in the given contours. In order to facilitate the derivation of features that capture the characteristics of shape roughness of contours of breast masses, methods to derive a signature based on the turning angle function obtained from the polygonal model are described. Methods are also described to derive an index of spiculation, an index characterizing the presence of convex regions, an index characterizing the presence of concave regions, an index of convexity, and a measure of fractal dimension from the turning angle function. Results of testing the methods with a set of 111 contours of 65 benign masses and 46 malignant tumors are presented and discussed. It is shown that shape modeling and analysis can lead to classification accuracy in discriminating between benign masses and malignant tumors, in terms of the area under the receiver operating characteristic curve, of up to 0.94. The methods have applications in modeling and analysis of the shape of various types of regions or objects in images, computer vision, computer graphics, and analysis of biomedical images, with particular significance in computer-aided diagnosis of breast cancer. Table of Contents: Analysis of Shape / Polygonal Modeling of Contours / Shape Factors for Pattern Classification / Classification of Breast Masses

Digital Mammography

Etta D. Pisano,Martin Joel Yaffe,Cherie M. Kuzmiak
Digital Mammography Book PDF

Author : Etta D. Pisano,Martin Joel Yaffe,Cherie M. Kuzmiak
Publisher : Lippincott Williams & Wilkins
Page : 24 pages
File Size : 52,9 Mb
Release : 2004
Category : Medical
ISBN : 9780781741422

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Digital Mammography by Etta D. Pisano,Martin Joel Yaffe,Cherie M. Kuzmiak Pdf

Bogen er en grundlæggende lærebog om digital mammografi, hvori digital mammografi og traditionel mammografi også sammenlignes i forhold til screening, diagnoser og radiografisk billedteknik. Der er en komplet billedsamling af cases indenfor digital mammografi.

Optimization in Machine Learning and Applications

Anand J. Kulkarni,Suresh Chandra Satapathy
Optimization in Machine Learning and Applications Book PDF

Author : Anand J. Kulkarni,Suresh Chandra Satapathy
Publisher : Springer Nature
Page : 202 pages
File Size : 44,8 Mb
Release : 2019-11-29
Category : Technology & Engineering
ISBN : 9789811509940

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Optimization in Machine Learning and Applications by Anand J. Kulkarni,Suresh Chandra Satapathy Pdf

This book discusses one of the major applications of artificial intelligence: the use of machine learning to extract useful information from multimodal data. It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The book also presents formulations of real-world machine learning problems, and discusses AI solution methodologies as standalone or hybrid approaches. Lastly, it proposes novel metaheuristic methods to solve complex machine learning problems. Featuring valuable insights, the book helps readers explore new avenues leading toward multidisciplinary research discussions.

Breast Cancer Screening and Diagnosis

Mahesh K Shetty
Breast Cancer Screening and Diagnosis Book PDF

Author : Mahesh K Shetty
Publisher : Springer
Page : 458 pages
File Size : 46,6 Mb
Release : 2014-09-19
Category : Medical
ISBN : 9781493912674

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Breast Cancer Screening and Diagnosis by Mahesh K Shetty Pdf

This book presents the current trends and practices in breast imaging. Topics include mammographic interpretation; breast ultrasound; breast MRI; management of the symptomatic breast in young, pregnant and lactating women; breast intervention with imaging pathological correlation; the postoperative breast and current and emerging technologies in breast imaging. It emphasizes the importance of fostering a multidisciplinary approach in the diagnosis and treatment of breast diseases. Featuring more than 800 high-resolution images and showcasing contributions from leading authorities in the screening, diagnosis and management of the breast cancer patient, Breast Cancer Screening and Diagnosis is a valuable resource for radiologists, oncologists and surgeons.

Contrast-Enhanced Mammography

Marc Lobbes,Maxine S. Jochelson
Contrast Enhanced Mammography Book PDF

Author : Marc Lobbes,Maxine S. Jochelson
Publisher : Springer
Page : 160 pages
File Size : 55,6 Mb
Release : 2019-04-29
Category : Medical
ISBN : 9783030110635

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Contrast-Enhanced Mammography by Marc Lobbes,Maxine S. Jochelson Pdf

This book is a comprehensive guide to contrast-enhanced mammography (CEM), a novel advanced mammography technique using dual-energy mammography in combination with intravenous contrast administration in order to increase the diagnostic performance of digital mammography. Readers will find helpful information on the principles of CEM and indications for the technique. Detailed attention is devoted to image interpretation, with presentation of case examples and highlighting of pitfalls and artifacts. Other topics to be addressed include the establishment of a CEM program, the comparative merits of CEM and MRI, and the roles of CEM in screening populations and monitoring of response to neoadjuvant chemotherapy. CEM became commercially available in 2011 and is increasingly being used in clinical practice owing to its superiority over full-field digital mammography. This book will be an ideal source of knowledge and guidance for all who wish to start using the technique or to learn more about it.