Non-Linear Filters for Mammogram Enhancement - A Robust Computer-aided Analysis Framework for Early Detection of Breast Cancer (Paperback, 1st ed. 2020)

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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 of the most challenging research domains in image processing.

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Product Description

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.

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Product Details

General

Imprint

Springer Verlag, Singapore

Country of origin

Singapore

Series

Studies in Computational Intelligence, 861

Release date

November 2020

Availability

Expected to ship within 10 - 15 working days

First published

2020

Authors

, ,

Dimensions

235 x 155mm (L x W)

Format

Paperback

Pages

239

Edition

1st ed. 2020

ISBN-13

978-981-15-0444-0

Barcode

9789811504440

Categories

LSN

981-15-0444-X



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