Mammographic Image Analysis
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Mammographic Image Analysis
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Author : R. Highnam
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Mammographic Image Analysis written by R. Highnam and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Medical categories.
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.
State Of The Art In Digital Mammographic Image Analysis
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Author : K W Bowyer
language : en
Publisher: World Scientific
Release Date : 1994-07-26
State Of The Art In Digital Mammographic Image Analysis written by K W Bowyer and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-07-26 with Computers categories.
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. Contents:Automation in Mammography: Computer Vision and Human Perception (S Astley et al.)Restoration of Mammographic Images in the Presence of Signal-Dependent Noise (F Aghdasi et al.)Computer-Aided Detection and Diagnosis of Masses and Clustered Microcalcifications from Digital Mammograms (R M Nishikawa et al.)Feature Extraction for Computer-Aided Analysis of Mammograms (H Bårman et al.)Detection and Classification of Mammographic Calcifications (L Shen et al.)Comparative Evaluation of Pattern Recognition Techniques for Detection of Microcalcifications in Mammography (K S Woods et al.)Automated Detection of Breast Asymmetry Using Anatomical Features (P Miller & S Astley)Image Processing and Computer Aided Diagnosis in Digital Mammography “A Radiologist's Perspective” (E D Pisano & F Shtern)and other papers Readership: Computer scientists and biomedical engineers. keywords:Mammography;Digital;Analysis;Processing;Detection;Computer Vision;Image;Breast;Mammographic Image Analysis;Computer-Aided Diagnosis;Digital Mammography;Medical Image Analysis
Mammographic Image Analysis
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Author : Ralph Highnam
language : en
Publisher: Springer Science & Business Media
Release Date : 1999
Mammographic Image Analysis written by Ralph Highnam and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Health & Fitness categories.
The key contribution of the approach to x-ray mammographic image analysis developed in this monograph is a representation of the non-fatty compressed breast tissue that we show can be derived from a single mammogram. The importance of the representation, called hint, is that it removes all those changes in the image that are due only to the particular imaging conditions (for example, the film speed or exposure time), leaving just the non-fatty 'interesting' tissue. Normalising images in this way enables them to be enhanced and matched, and regions in them to be classified more reliably, because unnecessary, distracting variations have been eliminated. Part I of the monograph develops a model-based approach to x-ray mammography, Part II shows how it can be put to work successfully on a range of clinically-important tasks, while Part III develops a model and exploits it for contrast-enhanced MRI mammography. The final chapter points the way forward in a number of promising areas of research.
Mammographic Image Analysis
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Author : R. Highnam
language : en
Publisher: Springer
Release Date : 2012-10-14
Mammographic Image Analysis written by R. Highnam and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-14 with Medical categories.
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.
Computerized Analysis Of Mammographic Images For Detection And Characterization Of Breast Cancer
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Author : Paola Casti
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2017-07-06
Computerized Analysis Of Mammographic Images For Detection And Characterization Of Breast Cancer written by Paola Casti and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-06 with Technology & Engineering categories.
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
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Author : 陈智丽
language : en
Publisher:
Release Date : 2020
Mammographic Image Analysis written by 陈智丽 and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Breast categories.
Classification Of Mammogram Images
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Author : Supriya Salve
language : en
Publisher: diplom.de
Release Date : 2017-03-23
Classification Of Mammogram Images written by Supriya Salve and has been published by diplom.de this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-23 with Medical categories.
Breast cancer is the most common type of cancer in women, which also causes the most cancer deaths among them today. Mammography is the only reliable method to detect breast cancer in the early stage among all diagnostic methods available currently. Breast cancer can occur in both men and women and is defined as an abnormal growth of cells in the breast that multiply uncontrollably. The main factors which cause breast cancer are either hormonal or genetic. Masses are quite subtle, and have many shapes such as circumscribed, speculated or ill-defined. These tumors can be either benign or malignant. Computer-aided methods are powerful tools to assist the medical staff in hospitals and lead to better and more accurate diagnosis. The main objective of this research is to develop a Computer Aided Diagnosis (CAD) system for finding the tumors in the mammographic images and classifying the tumors as benign or malignant. There are five main phases involved in the proposed CAD system: image pre-processing, extraction of features from mammographic images using Gabor Wavelet and Discrete Wavelet Transform (DWT), dimensionality reduction using Principal Component Analysis (PCA) and classification using Support Vector Machine (SVM) classifier.
Non Linear Filters For Mammogram Enhancement
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Author : Vikrant Bhateja
language : en
Publisher: Springer Nature
Release Date : 2019-11-02
Non Linear Filters For Mammogram Enhancement written by Vikrant Bhateja and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-02 with Technology & Engineering categories.
This book presents non-linear image enhancement approaches to mammograms as a robust computer-aided analysis solution for the early detection of breast cancer, and provides a compendium of non-linear mammogram enhancement approaches: from the fundamentals to research challenges, practical implementations, validation, and advances in applications. The book includes a comprehensive discussion on breast cancer, mammography, breast anomalies, and computer-aided analysis of mammograms. It also addresses fundamental concepts of mammogram enhancement and associated challenges, and features a detailed review of various state-of-the-art approaches to the enhancement of mammographic images and emerging research gaps. Given its scope, the book offers a valuable asset for radiologists and medical experts (oncologists), as mammogram visualization can enhance the precision of their diagnostic analyses; and for researchers and engineers, as the analysis of non-linear filters is one of the most challenging research domains in image processing.
Physics Of Mammographic Imaging
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Author : Mia K. Markey
language : en
Publisher: CRC Press
Release Date : 2012-11-09
Physics Of Mammographic Imaging written by Mia K. Markey and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-09 with Science categories.
Due to the increasing number of digital mammograms and the advent of new kinds of three-dimensional x-ray and other forms of medical imaging, mammography is undergoing a dramatic change. To meet their responsibilities, medical physicists must constantly renew their knowledge of advances in medical imaging or radiation therapy, and must be prepared to function at the intersection of these two fields. Physics of Mammographic Imaging gives an overview on the current role and future potential of new alternatives to mammography in the context of clinical need, complementary approaches, and ongoing research. This book provides comprehensive coverage on the fundamentals of image formation, image interpretation, analysis, and modeling. It discusses the use of mammographic imaging in the detection, diagnosis, treatment planning, and monitoring of breast cancer. Expert authors give a balanced summary of core topics such as digital mammography, contrast-enhanced mammography, stereomammography, breast tomosynthesis, and breast CT. The book highlights the use of mammographic imaging with complementary breast imaging modalities such as ultrasound, MRI, and nuclear medicine techniques. It discusses critical issues such as computer-aided diagnosis, perception, and quality assurance. This is an exciting time in the development of medical imaging, with many new technologies poised to make a substantial impact on breast cancer care. This book will help researchers and students get up to speed on crucial developments and contribute to future advances in the field.
Analysis Of Oriented Texture With Application To The Detection Of Architectural Distortion In Mammograms
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Author : Fabio Ayres
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Analysis Of Oriented Texture With Application To The Detection Of Architectural Distortion In Mammograms written by Fabio Ayres and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Technology & Engineering categories.
The presence of oriented features in images often conveys important information about the scene or the objects contained; the analysis of oriented patterns is an important task in the general framework of image understanding. As in many other applications of computer vision, the general framework for the understanding of oriented features in images can be divided into low- and high-level analysis. In the context of the study of oriented features, low-level analysis includes the detection of oriented features in images; a measure of the local magnitude and orientation of oriented features over the entire region of analysis in the image is called the orientation field. High-level analysis relates to the discovery of patterns in the orientation field, usually by associating the structure perceived in the orientation field with a geometrical model. This book presents an analysis of several important methods for the detection of oriented features in images, and a discussion of the phase portrait method for high-level analysis of orientation fields. In order to illustrate the concepts developed throughout the book, an application is presented of the phase portrait method to computer-aided detection of architectural distortion in mammograms. Table of Contents: Detection of Oriented Features in Images / Analysis of Oriented Patterns Using Phase Portraits / Optimization Techniques / Detection of Sites of Architectural Distortion in Mammograms