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
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