Titlebook: Non-Linear Filters for Mammogram Enhancement; A Robust Computer-ai Vikrant Bhateja,Mukul Misra,Shabana Urooj Book 2020 Springer Nature Sing

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Quantitative Metrics for Mammographic Image Quality AssessmentThe performance of the mammogram enhancement approaches is objectively evaluated as well as benchmarked using various objective IQA metrics to quantify contrast enhancement, edge enhancement and signal-to-noise ratios (Hwang and Peli .).

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Mammogram Benchmarking DatabasesThe usage of internationally acclaimed mammographic databases is important in order to ensure validations and comparison of response from various studies.

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Design Objectives and Methodology for Computer-aided Analysis of MammogramsThe aim of the research work presented in this book is to provide a reliable CAD solution for breast cancer performing enhancement for automated analysis of mammograms.

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Non-Linear Polynomial Filters: Overview, Evolution and Proposed Mathematical FormulationLast few decades have marked growing interest towards developments in signal processing techniques on account of the diverse spread in multimedia applications (which includes image and video processing).

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Non-Linear Polynomial Filters for Contrast Enhancement of MammogramsIt is known that the characteristic equation of Non-linear Polynomial Filters (NPF) can be conceptualized as a combination of linear and quadratic terms.

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https://doi.org/10.1007/978-981-15-0442-6Breast Cancer Diagnostics; Mammogram Enhancement; Image Quality Assessment; Mammography; Non-linear Filt

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s data protection by design and a corresponding data protection impact assessment that details security and privacy by design for a project processing data. Security and privacy of data in the Internet of Medical Things (IoMT) handles sensitive health data and accordingly is bound by additional regu

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