Cerebella segmentation on MR images of pediatric patients with medulloblastoma

Shan, Zu Y., Ji, Qing, Glass, John, Gajar, Amar and Reddick, Wilburn E. (2005). Cerebella segmentation on MR images of pediatric patients with medulloblastoma. In: Medical Imaging 2005: Image Processing. Medical Imaging 2005, San Diego, CA, United States, (1582-1588). 15-17 February 2005. doi:10.1117/12.594661

Author Shan, Zu Y.
Ji, Qing
Glass, John
Gajar, Amar
Reddick, Wilburn E.
Title of paper Cerebella segmentation on MR images of pediatric patients with medulloblastoma
Conference name Medical Imaging 2005
Conference location San Diego, CA, United States
Conference dates 15-17 February 2005
Proceedings title Medical Imaging 2005: Image Processing
Journal name Progress in Biomedical Optics and Imaging
Place of Publication Bellingham, WA, United States
Publisher SPIE - International Society for Optical Engineering
Publication Year 2005
Sub-type Fully published paper
DOI 10.1117/12.594661
ISBN 0-8194-5721-3
ISSN 1605-7422
Volume 5747
Start page 1582
End page 1588
Total pages 7
Language eng
Abstract/Summary In this study, an automated method has been developed to identify the cerebellum from T1-weighted MR brain images of patients with medulloblastoma. A new objective function that is similar to Gibbs free energy in classic physics was defined; and the brain structure delineation was viewed as a process of minimizing Gibbs free energy. We used a rigid- body registration and an active contour (snake) method to minimize the Gibbs free energy in this study. The method was applied to 20 patient data sets to generate cerebellum images and volumetric results. The generated cerebellum images were compared with two manually drawn results. Strong correlations were found between the automatically and manually generated volumetric results, the correlation coefficients with each of manual results were 0.971 and 0.974, respectively. The average Jaccard similarities with each of two manual results were 0.89 and 0.88, respectively. The average Kappa indexes with each of two manual results were 0.94 and 0.93, respectively. These results showed this method was both robust and accurate for cerebellum segmentation. The method may be applied to various research and clinical investigation in which cerebellum segmentation and quantitative MR measurement of cerebellum are needed.
Keyword Automated brain segmentation
Magnetic resonance imaging (MRI)
Active contour
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status Non-UQ

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