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020 _a9789811504426
024 7 _a10.1007/978-981-15-0442-6
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
041 0 _aeng
050 4 _aRG493.5.R33
_b2020 EB
100 1 _aBhateja, Vikrant
_eautor
_999448
245 1 0 _aNon-Linear Filters for Mammogram Enhancement :
_bA Robust Computer-aided Analysis Framework for Early Detection of Breast Cancer
_cby Vikrant Bhateja, Mukul Misra, Shabana Urooj
250 _aFirst edition
264 1 _aSingapore
_bSpringer Singapore :
_bImprint: Springer
_c2020.
300 _a1 recurso en línea (XXVIII, 239 páginas)
336 _2rdacontent
_aTexto
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
347 _atext file
_bPDF
490 0 _aStudies in Computational Intelligence
_x1860-949X
_v861
490 0 _aIntelligent Technologies and Robotics (Springer-42732)
505 0 _aIntroduction: 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 3 _aThis 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. .
988 _aPrimersemestre_2020_Robotics
650 7 _2embne
_9147244
_aMamografía
650 7 _2embne
_9311728
_aCáncer
_xDiagnóstico por imagen
700 1 _aMisra, Mukul
_eautor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aUrooj, Shabana
_eautor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9789811504419
776 0 8 _iPrinted edition:
_z9789811504433
776 0 8 _iPrinted edition:
_z9789811504440
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-15-0442-6
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
_n0
998 _b03/2020
_dz
_eb
_zSI