A Robust Computer-aided Analysis Framework for Early Detection of Breast Cancer
1. Auflage 2020,
Band: 861, 239 Seiten, Kartoniert, Paperback, Format (B × H): 157 mm x 235 mm, Gewicht: 415 g
Reihe: Studies in Computational Intelligence
Verlag: Springer, Berlin
Bhateja / Misra / Urooj Non-Linear Filters for Mammogram Enhancement
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.
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.