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Non-linear filters for mammogram enh...

Bhateja, Vikrant.

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

Record Type:	Electronic resources : Monograph/item
Title/Author:	Non-linear filters for mammogram enhancement/ by Vikrant Bhateja, Mukul Misra, Shabana Urooj.
Reminder of title:	a robust computer-aided analysis framework for early detection of breast cancer /
Author:	Bhateja, Vikrant.
other author:	Misra, Mukul.
Published:	Singapore :Springer Singapore : : 2020.,
Description:	xxviii, 239 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer eBooks
Subject:	Breast - Radiography. -
Online resource:	https://doi.org/10.1007/978-981-15-0442-6
ISBN:	9789811504426

Non-linear filters for mammogram enhancement = a 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.861..

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

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

832754
Breast
--Radiography.

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

Dewey Class. No.: 618.190754

Non-linear filters for mammogram enhancement = a robust computer-aided analysis framework for early detection of breast cancer /
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100 1 $a Bhateja, Vikrant. $3 2200044
245 1 0 $a Non-linear filters for mammogram enhancement $h [electronic resource] : $b a robust computer-aided analysis framework for early detection of breast cancer / $c by Vikrant Bhateja, Mukul Misra, Shabana Urooj.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2020.
300 $a xxviii, 239 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-949X ; $v v.861
505 0 $a 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.
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.
650 0 $a Breast $x Radiography. $3 832754
650 0 $a Image analysis. $3 561018
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Image Processing and Computer Vision. $3 891070
650 2 4 $a Diagnostic Radiology. $3 891111
650 2 4 $a Cancer Research. $3 891172
700 1 $a Misra, Mukul. $3 3444554
700 1 $a Urooj, Shabana. $3 3297641
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830 0 $a Studies in computational intelligence ; $v v.861. $3 3444555
856 4 0 $u https://doi.org/10.1007/978-981-15-0442-6
950 $a Intelligent Technologies and Robotics (Springer-42732)