UID:
almahu_9949419881302882
Format:
XIII, 302 p. 97 illus., 45 illus. in color.
,
online resource.
Edition:
1st ed. 2023.
ISBN:
9783031194252
Content:
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. This book also: Enriches reader understanding of the latest fuzzy sets methods using higher level information (object or scene level) for advanced tasks, such as image understanding Shares many insights into fuzzy spatial objects, including fuzzy geometry and topology as well as set theoretical operations Covers in detail machine learning in image processing and understanding, with special focus on clustering, classification, and basic and advanced fuzzy methods .
Note:
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.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9783031194245
Additional Edition:
Printed edition: ISBN 9783031194269
Additional Edition:
Printed edition: ISBN 9783031194276
Language:
English
DOI:
10.1007/978-3-031-19425-2
URL:
https://doi.org/10.1007/978-3-031-19425-2
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