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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 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 ofthe most challenging research domains in image processing.
| Autorius: | Vikrant Bhateja, Shabana Urooj, Mukul Misra, |
| Serija: | Studies in Computational Intelligence |
| Leidėjas: | Springer Nature Singapore |
| Išleidimo metai: | 2020 |
| Knygos puslapių skaičius: | 268 |
| ISBN-10: | 981150444X |
| ISBN-13: | 9789811504440 |
| Formatas: | 235 x 155 x 15 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Non-Linear Filters for Mammogram Enhancement: A Robust Computer-aided Analysis Framework for Early Detection of Breast Cancer“
