Optimal Multilevel Threshold Selection for Brain MR Image Segmentation

Language: English

Published by LAP LAMBERT Academic Publishing Mrz 2019, 2019

6139970466 / 9786139970469

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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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This item is printed on demand - it takes 3-4 days longer - Neuware -Medical image processing is one of the real research regions in the most recent four decades. Segmentation partitions an image into constituent parts. This basic operation helps to analyze and interpret a certain region of interest of an image. Image segmentation helps in diagnosing abnormality in brain or any part of the body from the MRI scan or PET scan. Presently MRI is the most popular clinical diagnostic procedure for detection of any brain disorder, as it is a complete non-invasive method. Moreover, its ability to produce high resolution spatial images and its sensitivity towards differentiating neurological tissues help in diagnosis, prognosis, pre-surgical and post-surgical treatment planning for various diseases. If image segmentation can be done in an effective way, then the lesions, or the disorder, if present, can be classified to an effectual micro-level. This book presents a fast and efficient nature inspired optimization approaches for the optimal selection of threshold levels for brain MR image pre segmentation. We hope this book is most useful for the researchers and masters level students who were in the area of digital image processing. 96 pp. Englisch.

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Title
Optimal Multilevel Threshold Selection for Brain MR Image Segmentation
Author
Satish Kumar Injeti
Publisher
LAP LAMBERT Academic Publishing Mrz 2019
Publication year
2019
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6139970466
ISBN 13
9786139970469
Item weight
161 grams
Dimensions
220x150x6 mm

BuchWeltWeit Ludwig Meier e.K.

Bergisch Gladbach, Germany

5-star seller

AbeBooks seller since January 11, 2012

Shipping rates from Germany to U.S.A.

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BuchWeltWeit Ludwig Meier e.K.

Germany