
Fuzzy Sets Methods in Image Processing and Understanding
Medical Imaging Applications
Springer (Publisher)
Published on 2. January 2023
Book
Hardback
XIII, 302 pages
978-3-031-19424-5 (ISBN)
Description
This book provides a thorough overview of recent methods using higher level information (object or scene level) for advanced tasks such as image understanding along with their applications to medical images. Advanced methods for fuzzy image processing and understanding are presented, including fuzzy spatial objects, geometry and topology, mathematical morphology, machine learning, verbal descriptions of image content, fusion, spatial relations, and structural representations. For each methodological aspect covered, illustrations from the medical imaging domain are provided. This is an ideal book for graduate students and researchers in the field of medical image processing.
More details
Edition
2023 ed.
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
52 s/w Abbildungen, 45 farbige Abbildungen
XIII, 302 p. 97 illus., 45 illus. in color.
Dimensions
Height: 241 mm
Width: 160 mm
Thickness: 23 mm
Weight
641 gr
ISBN-13
978-3-031-19424-5 (9783031194245)
DOI
10.1007/978-3-031-19425-2
Schweitzer Classification
Other editions
Additional editions

Isabelle Bloch | Anca Ralescu
Fuzzy Sets Methods in Image Processing and Understanding
Medical Imaging Applications
Book
01/2024
Springer
€149.79
Shipment within 15-20 days

Isabelle Bloch | Anca Ralescu
Fuzzy Sets Methods in Image Processing and Understanding
Medical Imaging Applications
E-Book
01/2023
Springer
€139.09
Available for download
Persons
Isabelle Bloch is a Professor at Telecom ParisTech.
Anca Ralescu is a Professor at the University of Cincinnati.
Anca Ralescu is a Professor at the University of Cincinnati.
Content
Introduction.- Preliminaries.- Fuzzy spatial objects (fuzzy geometry and topology, set theoretic operations).- Mathematical morphology.- Distances and similarities between fuzzy sets.- Machine learning in image processing and understanding.- Fusion.- Spatial relations.- Structural representations.