A knowledge-guided active contour method of segmentation of cerebella on MR images of pediatric patients with medulloblastoma

Shan, Zu Y., Ji, Qing, Gajjar, Amar Gajjar and Reddick, Wilburn E. (2005) A knowledge-guided active contour method of segmentation of cerebella on MR images of pediatric patients with medulloblastoma. Journal of Magnetic Resonance Imaging, 21 1: 1-11.


Author Shan, Zu Y.
Ji, Qing
Gajjar, Amar Gajjar
Reddick, Wilburn E.
Title A knowledge-guided active contour method of segmentation of cerebella on MR images of pediatric patients with medulloblastoma
Journal name Journal of Magnetic Resonance Imaging  (ERA 2012 Listed)    (ERA 2010 Rank B)   Check publisher's open access policy
Publication date 2005-01
Sub-type Article
Year available 2004
DOI 10.1002/jmri.20229
Volume number 21
Issue number 1
ISSN 1053-1807; 1522-2586
Start page 1
End page 11
Total pages 11
Place of publication Hoboken, NJ, United States
Publisher John Wiley & Sons
Language eng
Formatted abstract Purpose: To develop an automated method for identification of the cerebella on magnetic resonance (MR) images of patients with medulloblastoma.
Materials and Methods: The method used a template constructed from 10 patients’ aligned MR head images, and the contour of this template was superimposed on the aligned data set of a given patient as the starting contour. The starting contour was then actively adjusted to locate the boundary of the cerebellum of the given patient. Morphologic operations were applied to the outlined volume to generate cerebellum images. The method was then applied to data sets of 20 other patients to
generate cerebellum images and volumetric results.
Results: Comparison of the automatically generated cerebellum images with two sets of manually traced images showed a strong correlation between the automatically and
manually generated volumetric results (correlation coefficient, 0.97). The average Jaccard similarities were 0.89 and 0.88 in comparison to each of two manually traced images, respectively. The same comparisons yielded average kappa indexes of 0.94 and 0.93, respectively.
Conclusion: The method was robust and accurate for cerebellum segmentation on MR images of patients with medulloblastoma. The method may be applied to investigations that require segmentation and quantitative measurement of MR images of the cerebellum.
Keyword Automated brain segmentation
Magnetic resonance imaging (MRI)
Cerebellum
Active contour
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ
Additional Notes Article first published online: 20 DEC 2004

Document type: Journal Article
Sub-type: Article
Collections: ERA 2012 Admin Only
Centre for Advanced Imaging Publications
 
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