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Non-linear filters for mammogram enhancement : a robust computer-aided analysis framework for early detection of breast cancer

Author: Vikrant Bhateja; Mukul Misra; Shabana Urooj
Publisher: Singapore : Springer, [2020]
Series: Studies in computational intelligence, v. 861.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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,  Read more...
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Genre/Form: Electronic books
Additional Physical Format: (OCoLC)1113879095
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Vikrant Bhateja; Mukul Misra; Shabana Urooj
ISBN: 9789811504426 9811504423
OCLC Number: 1126279440
Description: 1 online resource (xxviii, 239 pages) : illustrations (some color).
Contents: 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.
Series Title: Studies in computational intelligence, v. 861.
Responsibility: Vikrant Bhateja, Mukul Misra, Shabana Urooj.

Abstract:

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.

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