Semantic Parsing of Brain MR Images

C. Ledig; D. Rueckert

doi:10.1016/B978-0-12-802581-9.00014-7

Semantic Parsing of Brain MR Images

C. Ledig, D. Rueckert

Imperial College London

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

2 Scopus citations

Abstract

The semantic parsing of brain magnetic resonance images is an important step in many applications that require the segmentation of medical images. In this chapter, we describe the most commonly used approach for image segmentation, namely atlas-based segmentation. We discuss the main components of atlas-based segmentation, including atlas-to-image registration, label fusion, and atlas selection. In addition, we also review different brain atlases that are frequently used as anatomical priors in image segmentation of neuroanatomical structures.

Original language	English
Title of host publication	Medical Image Recognition, Segmentation and Parsing
Subtitle of host publication	Machine Learning and Multiple Object Approaches
Publisher	Elsevier
Pages	307-335
Number of pages	29
ISBN (Electronic)	9780128025819
ISBN (Print)	9780128026762
DOIs	https://doi.org/10.1016/B978-0-12-802581-9.00014-7
State	Published - 1 Jan 2015
Externally published	Yes

Keywords

Brain atlases
MR imaging
Machine learning
Registration
Segmentation

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10.1016/B978-0-12-802581-9.00014-7

Cite this

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KW - Brain atlases

KW - MR imaging

KW - Machine learning

KW - Registration

KW - Segmentation

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M3 - Chapter

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BT - Medical Image Recognition, Segmentation and Parsing

PB - Elsevier

ER -

Semantic Parsing of Brain MR Images

Abstract

Keywords

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