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Ihr Team von Sack Fachmedien
Bhateja / Misra / Urooj Non-Linear Filters for Mammogram Enhancement
Erscheinungsjahr 2019
ISBN: 978-981-15-0442-6
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark
A Robust Computer-aided Analysis Framework for Early Detection of Breast Cancer
E-Book, Englisch, 239 Seiten
Reihe: Studies in Computational Intelligence
ISBN: 978-981-15-0442-6
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark
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 ofthe most challenging research domains in image processing.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
Introduction: Computer-aided Analysis of Mammograms for Diagnosis of Breast Cancer.- Mammogram Enhancement: Background.- Methodology: Motivation, Objectives and Proposed Solution Approach.- Performance Evaluation and Benchmarking of Mammogram Enhancement Approaches: Mammographic Image Quality Assessment.- Non-linear Polynomial Filters: Overview, Evolution and Proposed Mathematical Formulation.- Non-linear Polynomial Filters for Contrast Enhancement of Mammograms.- Non-linear Polynomial Filters for Edge Enhancement of Mammograms.- Human Visual System Based Unsharp Masking for Enhancement of Mammograms.- Conclusions and Future Scope: Applications, Contributions and Impact.




