DocumentCode :
1379077
Title :
A geometric snake model for segmentation of medical imagery
Author :
Yezzi, Anthony, Jr. ; Kichenassamy, Satyanad ; Kumar, Arun ; Olver, Peter ; Tannenbaum, Allen
Author_Institution :
Dept. of Electr. Eng., Minnesota Univ., Minneapolis, MN, USA
Volume :
16
Issue :
2
fYear :
1997
fDate :
4/1/1997 12:00:00 AM
Firstpage :
199
Lastpage :
209
Abstract :
We employ the new geometric active contour models, previously formulated, for edge detection and segmentation of magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound medical imagery. Our method is based on defining feature-based metrics on a given image which in turn leads to a novel snake paradigm in which the feature of interest may be considered to lie at the bottom of a potential well. Thus, the snake is attracted very quickly and efficiently to the desired feature.
Keywords :
biomedical NMR; biomedical ultrasonics; computerised tomography; edge detection; feature extraction; image segmentation; medical image processing; CT; MRI; computed tomography; edge detection; feature-based metrics; geometric active contour models; geometric snake model; magnetic resonance imaging; medical imagery; potential well; segmentation; snake paradigm; ultrasound medical imagery; Active contours; Biomedical imaging; Computed tomography; Heart; Image edge detection; Image segmentation; Magnetic resonance imaging; Shape; Solid modeling; Ultrasonic imaging; Algorithms; Diagnostic Imaging; Humans; Image Processing, Computer-Assisted; Models, Statistical; Models, Theoretical; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Medical Imaging, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0062
Type :
jour
DOI :
10.1109/42.563665
Filename :
563665
Link To Document :
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