White matter lesion segmentation based on feature joint occurrence probability and χ2 random field theory from magnetic resonance (MR) images

Yang, Faguo, Shan, Zuyao and Kruggel, Frithjof (2010) White matter lesion segmentation based on feature joint occurrence probability and χ2 random field theory from magnetic resonance (MR) images. Pattern Recognition Letters, 31 9: 781-790. doi:10.1016/j.patrec.2010.01.025

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Author Yang, Faguo
Shan, Zuyao
Kruggel, Frithjof
Title White matter lesion segmentation based on feature joint occurrence probability and χ2 random field theory from magnetic resonance (MR) images
Formatted title
White matter lesion segmentation based on feature joint occurrence probability and χ2 random field theory from magnetic resonance (MR) images
Journal name Pattern Recognition Letters   Check publisher's open access policy
ISSN 0167-8655
1872-7344
Publication date 2010-07-01
Sub-type Article (original research)
DOI 10.1016/j.patrec.2010.01.025
Volume 31
Issue 9
Start page 781
End page 790
Total pages 10
Place of publication Amsterdam, Netherlands
Publisher Elsevier BV
Language eng
Formatted abstract
Lesions of the brain's white matter are common findings in MR examinations of elderly subjects. A fully automatic method for segmenting white matter lesions is proposed here. The joint probability of multi-modality MR image intensities is used as a feature to segment lesions, because lesion intensities usually are outliers of the normal tissue intensities and the lesions' joint intensity probability appears much smaller than those of normal brain tissues. The χ2 random field theory is used to determine the significance of a detected lesion and provides a strict statistical analysis to exclude small-sized false-positive lesions. Experimental results show that the automatic segmentation of lesions is in high agreement with manual segmentation, and the χ2 random-field-based statistical analysis greatly improves lesion segmentation results.
Keyword White matter lesions
Joint probability
χ2 Random field theory
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: ERA 2012 Admin Only
Centre for Advanced Imaging Publications
 
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Citation counts: TR Web of Science Citation Count  Cited 9 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 9 times in Scopus Article | Citations
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