Segmentation: Principles and Basic Techniques
The purpose of image segmentation is to generate pixel agglomerations from an image that constitute parts of depicted objects. In medical imaging, segmentation often refers to the delineation of specific structures. Hence, it includes parts of classification as well. Segmentation strategies in medic...
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Published in | Guide to Medical Image Analysis pp. 209 - 247 |
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Main Author | |
Format | Book Chapter |
Language | English |
Published |
United Kingdom
Springer London, Limited
2017
Springer London |
Series | Advances in Computer Vision and Pattern Recognition |
Subjects | |
Online Access | Get full text |
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Summary: | The purpose of image segmentation is to generate pixel agglomerations from an image that constitute parts of depicted objects. In medical imaging, segmentation often refers to the delineation of specific structures. Hence, it includes parts of classification as well. Segmentation strategies in medical imaging combine data knowledge with domain knowledge to arrive at the result. Data knowledge refers to assumptions about continuity, homogeneity, and local smoothness of image features within segments. Domain knowledge represents information about the objects to be delineated. In this chapter, basic strategies for integrating the two types of knowledge into the segmentation process will be discussed. We will also describe basic segmentation methods that are popular in medical image analysis. |
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ISBN: | 9781447173182 144717318X |
ISSN: | 2191-6586 2191-6594 |
DOI: | 10.1007/978-1-4471-7320-5_6 |