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