DocumentCode :
1401612
Title :
Precise segmentation of the lateral ventricles and caudate nucleus in MR brain images using anatomically driven histograms
Author :
Worth, Andrew J. ; Makris, Nikos ; Patti, Mark R. ; Goodman, Julie M. ; Hoge, Elizabeth A. ; Caviness, Verne S., Jr. ; Kennedy, David N.
Author_Institution :
Center for Morphometric Anal., Massachusetts Gen. Hosp., Boston, MA, USA
Volume :
17
Issue :
2
fYear :
1998
fDate :
4/1/1998 12:00:00 AM
Firstpage :
303
Lastpage :
310
Abstract :
This paper demonstrates a time-saving, automated method that helps to segment the lateral ventricles and caudate nucleus in T1-weighted coronal magnetic resonance (MR) brain images of normal control subjects. The method involves choosing intensity thresholds by using anatomical information and by locating peaks in histograms. To validate the method, the lateral ventricles and caudate nucleus were segmented in three brain scans by four experts, first using an established method involving isointensity contours and manual editing, and second using automatically generated intensity thresholds as an aid to the established method. The results demonstrate both time savings and increased reliability.
Keywords :
biomedical NMR; brain; image segmentation; medical image processing; MR brain images; MRI; T1-weighted coronal magnetic resonance brain images; anatomically driven histograms; automatically generated intensity thresholds; caudate nucleus; lateral ventricles; medical diagnostic imaging; neuromorphometry; normal control subjects; precise segmentation; time-saving automated method; Automatic control; Automation; Brain; Histograms; Hospitals; Image segmentation; Magnetic resonance; Magnetic resonance imaging; Neuroscience; Noise robustness; Adult; Algorithms; Caudate Nucleus; Cerebral Ventricles; Child; Corpus Callosum; Female; Humans; Image Enhancement; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Male; Reproducibility of Results; Time Factors;
fLanguage :
English
Journal_Title :
Medical Imaging, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0062
Type :
jour
DOI :
10.1109/42.700743
Filename :
700743
Link To Document :
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