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Record Nr. |
UNINA9910483740603321 |
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Autore |
Bhateja Vikrant |
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Titolo |
Non-Linear Filters for Mammogram Enhancement : A Robust Computer-aided Analysis Framework for Early Detection of Breast Cancer / / by Vikrant Bhateja, Mukul Misra, Shabana Urooj |
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Pubbl/distr/stampa |
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Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (xxviii, 239 pages) : illustrations |
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Collana |
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Studies in Computational Intelligence, , 1860-949X ; ; 861 |
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Disciplina |
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Soggetti |
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Computational intelligence |
Optical data processing |
Radiology |
Cancer research |
Computational Intelligence |
Image Processing and Computer Vision |
Diagnostic Radiology |
Cancer Research |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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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. |
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Sommario/riassunto |
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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 |
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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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