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Non-linear filters for mammogram enh...

Bhateja, Vikrant.

Non-linear filters for mammogram enhancementa robust computer-aided analysis framework for early detection of breast cancer /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Non-linear filters for mammogram enhancementby Vikrant Bhateja, Mukul Misra, Shabana Urooj.
其他題名:	a robust computer-aided analysis framework for early detection of breast cancer /
作者:	Bhateja, Vikrant.
其他作者:	Misra, Mukul.
出版者:	Singapore :Springer Singapore :2020.
面頁冊數:	xxviii, 239 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	BreastRadiography.
電子資源:	https://doi.org/10.1007/978-981-15-0442-6
ISBN:	9789811504426$q(electronic bk.)

Non-linear filters for mammogram enhancementa robust computer-aided analysis framework for early detection of breast cancer /
Bhateja, Vikrant.

Non-linear filters for mammogram enhancementa robust computer-aided analysis framework for early detection of breast cancer /[electronic resource] :by Vikrant Bhateja, Mukul Misra, Shabana Urooj. - Singapore :Springer Singapore :2020. - xxviii, 239 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.8611860-949X ;. - Studies in computational intelligence ;v. 216..

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.

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.

ISBN: 9789811504426$q(electronic bk.)

Standard No.: 10.1007/978-981-15-0442-6doiSubjects--Topical Terms:

404856
Breast
--Radiography.

LC Class. No.: RG493.5.R33 / B43 2020

Dewey Class. No.: 618.190754

Non-linear filters for mammogram enhancementa robust computer-aided analysis framework for early detection of breast cancer /
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520 $a 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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