A knowledge-guided active model method of cortical structure segmentation on pediatric MR images

Shan, Zuyao, Parra, Carlos, Ji, Qing, Jain, Jinesh and Reddick, Wilburn E. (2006) A knowledge-guided active model method of cortical structure segmentation on pediatric MR images. Journal of Magnetic Resonance Imaging, 24 4: 779-789. doi:10.1002/jmri.20688


Author Shan, Zuyao
Parra, Carlos
Ji, Qing
Jain, Jinesh
Reddick, Wilburn E.
Title A knowledge-guided active model method of cortical structure segmentation on pediatric MR images
Journal name Journal of Magnetic Resonance Imaging   Check publisher's open access policy
ISSN 1053-1807
1522-2586
Publication date 2006-10
Sub-type Article (original research)
DOI 10.1002/jmri.20688
Volume 24
Issue 4
Start page 779
End page 789
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 quantification of cortical structures on pediatric MR images.

Materials and Methods:
A knowledge-guided active model (KAM) approach was proposed with a novel object function similar to the Gibbs free energy function. Triangular mesh models were transformed to images of a given subject by maximizing entropy, and then actively slithered to boundaries of structures by minimizing enthalpy. Volumetric results and image similarities of 10 different cortical structures segmented by KAM were compared with those traced manually. Furthermore, the segmentation performances of KAM and SPM2, (statistical parametric mapping, a MAT-LAB software package) were compared.

Results:
The averaged volumetric agreements between KAM- and manually-defined structures (both 0.95 for structures in healthy children and children with medulloblastoma) were higher than the volumetric agreement for SPM2 (0.90 and 0.80, respectively). The similarity measurements (kappa) between KAM- and manually-defined structures (0.95 and 0.93. respectively) were higher than those for SPM2 (both 0.86).

Conclusion: We have developed a novel automatic algorithm, KAM, for segmentation of cortical structures on MR images of pediatric patients. Our preliminary results indicated that when segmenting cortical structures, KAM was in better agreement with manually-delineated structures than SPM2. KAM can potentially be used to segment cortical structures for conformal radiation therapy planning and for quantitative evaluation of changes in disease or abnormality.
Keyword Automated structure segmentation
Magnetic resonance imaging (MRI)
Lobes active mesh
Cortical structures
Pediatric brain
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
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