Computational Intelligence and Modelling Techniques for Disease Detection in Mammogram Images



de

Éditeur :

Academic Press


Paru le : 2023-11-16



eBook Téléchargement , DRM LCP 🛈 DRM Adobe 🛈 ebook sans DRM
Lecture en ligne (streaming)
168,80

Téléchargement immédiat
Dès validation de votre commande
Ajouter à ma liste d'envies
Image Louise Reader présentation

Louise Reader

Lisez ce titre sur l'application Louise Reader.

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 learning 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 learning 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 learning and machine learning 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

Elsevier Science & Technology
Pages
280 pages
Collection
n.c
Parution
2023-11-16
Marque
Academic Press
EAN papier
9780443139994
EAN PDF
9780443140006

Informations sur l'ebook
Nombre pages copiables
28
Nombre pages imprimables
28
Taille du fichier
9411 Ko
Prix
168,80 €
EAN EPUB SANS DRM
9780443140006

Prix
168,80 €

Suggestions personnalisées