DocumentCode
406584
Title
Velocity-aided cardiac segmentation
Author
Cho, Jinsoo ; Brummer, Marijn ; Benkeser, Paul J.
Author_Institution
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
Volume
1
fYear
2003
fDate
17-21 Sept. 2003
Firstpage
622
Abstract
Segmentation of myocardial boundaries, especially the endocardial boundary, in images from magnetic resonance imaging (MRI) often suffers from flow-related signal loss, partial volume effects, and the presence of papillary muscles. To address these problems, a velocity-aided cardiac segmentation method based a modified active contour model with the orientation gradient force has been developed. Unlike other MRI cardiac segmentation methods based on active contour models, the velocity images from phase contrast MRI, together with the magnitude images, were used to derive an additional external force from the orientation gradient. The velocity images were also used to track the initial seed contours throughout the entire cardiac cycle to reduce the propagation of errors in sequential segmentation. The linear correlation coefficients and boundary matching descriptors of segmented boundaries were calculated relative to manually segmented reference boundaries to assess the accuracy of this method. Results of segmentation of the endocardial boundaries were encouraging in both individual frame segmentation and sequential frame segmentation.
Keywords
biomedical MRI; cardiology; image segmentation; image sequences; medical image processing; MRI; MRI cardiac segmentation methods; active contour model; boundary matching descriptors; cardiac cycle; endocardial! boundary; flow-related signal loss; individual frame segmentation; linear correlation coefficients; magnetic resonance imaging; myocardial boundaries segmentation; orientation gradient force; papillary muscles; partial volume effects; phase contrast MRI; segmented boundaries; sequential frame segmentation; sequential segmentation; velocity images; velocity-aided cardiac segmentation; Active contours; Biomedical computing; Biomedical engineering; Cardiac disease; Image edge detection; Image segmentation; Magnetic resonance imaging; Muscles; Myocardium; Radiology;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE
ISSN
1094-687X
Print_ISBN
0-7803-7789-3
Type
conf
DOI
10.1109/IEMBS.2003.1279830
Filename
1279830
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