DocumentCode :
1254757
Title :
Model creation and deformation for the automatic segmentation of the brain in MR images
Author :
Aboutanos, Georges B. ; Nikanne, Jyrki ; Watkins, Nancy ; Dawan, B.M.
Author_Institution :
Div. of Inf. Syst., Harris Corp., Melbourne, FL, USA
Volume :
46
Issue :
11
fYear :
1999
Firstpage :
1346
Lastpage :
1356
Abstract :
In this paper a method for the automatic segmentation of the brain in magnetic resonance images is presented and validated. The proposed method involves two steps: 1) the creation of an initial model, and 2) the deformation of this model to fit the exact contours of the brain in the images. A new method to create the initial model has been developed and compared to a more traditional approach in which initial models are created by means of brain atlases. A comprehensive validation of the complete segmentation method has been conducted on a series of three-dimensional T1-weighted magnetization-prepared rapid gradient echo image volumes acquired both from control volunteers and patients suffering from Cushing´s disease. This validation study compares results obtained with the method the authors propose and contours drawn manually. Averages differences between manual and automatic segmentation with the model creation method the authors propose are 1.7% and 2.7% for the control volunteers and the Cushing´s patients, respectively. These numbers are 1.8% and 5.6% when the atlas-based method is used.
Keywords :
biomedical MRI; brain models; diseases; image segmentation; medical image processing; 3D T1-weighted magnetization-prepared rapid gradient echo image volumes; Cushing´s disease patients; MRI; atlas-based method; automatic segmentation; brain MR images; control volunteers; magnetic resonance imaging; medical diagnostic imaging; model creation; model deformation; Automatic control; Biomedical imaging; Brain modeling; Deformable models; Image edge detection; Image processing; Image segmentation; Magnetic resonance; Surface fitting; Volume measurement; Algorithms; Brain; Cushing Syndrome; False Negative Reactions; False Positive Reactions; Humans; Magnetic Resonance Imaging; Models, Neurological; Observer Variation; Reference Values; Reproducibility of Results;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/10.797995
Filename :
797995
Link To Document :
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