Computational Intelligence and Modelling Techniques for Disease Detection in Mammogram Images

by: D. Jude Hemanth B.E. M.E. Ph.D (Editor)

Publisher: Academic Press

Edition: 1st

Publication Date: 2023/11/30

Language: English

Print Length: 348 pages

ISBN-10: 0443139997

ISBN-13: 9780443139994

Book Description

Computational Intelligence and Modelling Techniques for Disease Detection in Mammogram Images comprehensively examines the wide range of AI-based mammogram analysis methods for medical applications. Beginning with an introductory overview of mammogram data analysis, the book covers the current technologies such as ultrasound, molecular breast imaging (MBI), magnetic resonance (MR), and Positron Emission mammography (PEM), as well as the recent advancements in 3D breast tomosynthesis and 4D mammogram. Deep leaing models are presented in each chapter to show how they can assist in the efficient processing of breast images. The book also discusses hybrid intelligence approaches for early-stage detection and the use of machine leaing classifiers for cancer detection, staging and density assessment in order to develop a proper treatment plan. This book will not only aid computer scientists and medical practitioners in developing a real-time AI based mammogram analysis system, but also addresses the issues and challenges with the current processing methods which are not conducive for real-time applications.Presents novel ideas for AI based mammogram data analysisDiscusses the roles deep leaing and machine leaing techniques play in efficient processing of mammogram images and in the accurate defining of different types of breast cancerFeatures dozens of real-world case studies from contributors across the globe

About the Author

Computational Intelligence and Modelling Techniques for Disease Detection in Mammogram Images comprehensively examines the wide range of AI-based mammogram analysis methods for medical applications. Beginning with an introductory overview of mammogram data analysis, the book covers the current technologies such as ultrasound, molecular breast imaging (MBI), magnetic resonance (MR), and Positron Emission mammography (PEM), as well as the recent advancements in 3D breast tomosynthesis and 4D mammogram. Deep leaing models are presented in each chapter to show how they can assist in the efficient processing of breast images. The book also discusses hybrid intelligence approaches for early-stage detection and the use of machine leaing classifiers for cancer detection, staging and density assessment in order to develop a proper treatment plan. This book will not only aid computer scientists and medical practitioners in developing a real-time AI based mammogram analysis system, but also addresses the issues and challenges with the current processing methods which are not conducive for real-time applications.Presents novel ideas for AI based mammogram data analysisDiscusses the roles deep leaing and machine leaing techniques play in efficient processing of mammogram images and in the accurate defining of different types of breast cancerFeatures dozens of real-world case studies from contributors across the globe