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MRI segmentation of the human brain: challenges, methods, and applications

Ivana Despotovic, Bart Goossens UGent and Wilfried Philips UGent (2015) COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE.
abstract
Image segmentation is one of the most important tasks in medical image analysis and is often the first and the most critical step in many clinical applications. In brain MRI analysis, image segmentation is commonly used for measuring and visualizing the brain’s anatomical structures, for analyzing brain changes, for delineating pathological regions, and for surgical planning and image-guided interventions. In the last few decades, various segmentation techniques of different accuracy and degree of complexity have been developed and reported in the literature. In this paper we review the most popular methods commonly used for brain MRI segmentation. We highlight differences between them and discuss their capabilities, advantages, and limitations. To address the complexity and challenges of the brain MRI segmentation problem, we first introduce the basic concepts of image segmentation. Then, we explain different MRI preprocessing steps including image registration, bias field correction, and removal of nonbrain tissue. Finally, after reviewing different brain MRI segmentation methods, we discuss the validation problem in brain MRI segmentation.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
EXPECTATION-MAXIMIZATION ALGORITHM, IMAGE SEGMENTATION, AUTOMATIC SEGMENTATION, ACTIVE CONTOURS, LEVEL SET, TISSUE CLASSIFICATION, NONRIGID REGISTRATION, SPATIAL INFORMATION, NEONATAL BRAIN, VARYING STATISTICAL CLASSIFICATION
journal title
COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE
article number
450341
pages
23 pages
publisher
Hindawi Publishing Corporation
Web of Science type
Article
Web of Science id
000352390700001
DOI
10.1155/2015/450341
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
5835610
handle
http://hdl.handle.net/1854/LU-5835610
date created
2015-02-02 14:18:54
date last changed
2016-12-21 15:42:49
@article{5835610,
  abstract     = {Image segmentation is one of the most important tasks in medical image analysis and is often the first and the most critical step in many clinical applications. In brain MRI analysis, image segmentation is commonly used for measuring and visualizing the brain{\textquoteright}s anatomical structures, for analyzing brain changes, for delineating pathological regions, and for surgical planning and image-guided interventions. In the last few decades, various segmentation techniques of different accuracy and degree of complexity have been developed and reported in the literature. In this paper we review the most popular methods commonly used for brain MRI segmentation. We highlight differences between them and discuss their capabilities, advantages, and limitations. To address the complexity and challenges of the brain MRI segmentation problem, we first introduce the basic concepts of image segmentation. Then, we explain different MRI preprocessing steps including image registration, bias field correction, and removal of nonbrain tissue. Finally, after reviewing different brain MRI segmentation methods, we discuss the validation problem in brain MRI segmentation.},
  articleno    = {450341},
  author       = {Despotovic, Ivana and Goossens, Bart and Philips, Wilfried},
  journal      = {COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE},
  keyword      = {EXPECTATION-MAXIMIZATION ALGORITHM,IMAGE SEGMENTATION,AUTOMATIC SEGMENTATION,ACTIVE CONTOURS,LEVEL SET,TISSUE CLASSIFICATION,NONRIGID REGISTRATION,SPATIAL INFORMATION,NEONATAL BRAIN,VARYING STATISTICAL CLASSIFICATION},
  language     = {eng},
  pages        = {23},
  publisher    = {Hindawi Publishing Corporation},
  title        = {MRI segmentation of the human brain: challenges, methods, and applications},
  url          = {http://dx.doi.org/10.1155/2015/450341},
  year         = {2015},
}

Chicago
Despotovic, Ivana, Bart Goossens, and Wilfried Philips. 2015. “MRI Segmentation of the Human Brain: Challenges, Methods, and Applications.” Computational and Mathematical Methods in Medicine.
APA
Despotovic, I., Goossens, B., & Philips, W. (2015). MRI segmentation of the human brain: challenges, methods, and applications. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE.
Vancouver
1.
Despotovic I, Goossens B, Philips W. MRI segmentation of the human brain: challenges, methods, and applications. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE. Hindawi Publishing Corporation; 2015;
MLA
Despotovic, Ivana, Bart Goossens, and Wilfried Philips. “MRI Segmentation of the Human Brain: Challenges, Methods, and Applications.” COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE (2015): n. pag. Print.