Normalized Cuts in 3-D for Spinal MRI Segmentation
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Normalized Cuts in 3-D for Spinal MRI Segmentation. / Carballido-Gamio, Julio; Belongie, Serge J.; Majumdar, Sharmila.
In: IEEE Transactions on Medical Imaging, Vol. 23, No. 1, 01.2004, p. 36-44.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Normalized Cuts in 3-D for Spinal MRI Segmentation
AU - Carballido-Gamio, Julio
AU - Belongie, Serge J.
AU - Majumdar, Sharmila
N1 - Funding Information: Manuscript received December 17, 2002; revised June 20, 2003. This was supported in part by the National Institute on Aging (NIA) under Grant NIA-RO1-AG17762. The work of J. Carballido-Gamio was supported in part by the University of California under UC-Conacyt and Fulbright scholarships. The Associate Editor responsible for coordinating the review of this paper and recommending its publication was C. Meyer. Asterisk indicates corresponding author.
PY - 2004/1
Y1 - 2004/1
N2 - Segmentation of medical images has become an indispensable process to perform quantitative analysis of images of human organs and their functions. Normalized Cuts (NCut) is a spectral graph theoretic method that readily admits combinations of different features for image segmentation. The computational demand imposed by NCut has been successfully alleviated with the Nyström approximation method for applications different than medical imaging. In this paper we discuss the application of NCut with the Nyström approximation method to segment vertebral bodies from sagittal T1-weighted magnetic resonance images of the spine. The magnetic resonance images were preprocessed by the anisotropic diffusion algorithm, and three-dimensional local histograms of brightness was chosen as the segmentation feature. Results of the segmentation as well as limitations and challenges in this area are presented.
AB - Segmentation of medical images has become an indispensable process to perform quantitative analysis of images of human organs and their functions. Normalized Cuts (NCut) is a spectral graph theoretic method that readily admits combinations of different features for image segmentation. The computational demand imposed by NCut has been successfully alleviated with the Nyström approximation method for applications different than medical imaging. In this paper we discuss the application of NCut with the Nyström approximation method to segment vertebral bodies from sagittal T1-weighted magnetic resonance images of the spine. The magnetic resonance images were preprocessed by the anisotropic diffusion algorithm, and three-dimensional local histograms of brightness was chosen as the segmentation feature. Results of the segmentation as well as limitations and challenges in this area are presented.
KW - Magnetic resonance imaging (MRI)
KW - Normalized cuts (NCut)
KW - Nyström approximation method
KW - Segmentation
KW - Spine
UR - http://www.scopus.com/inward/record.url?scp=0346076622&partnerID=8YFLogxK
U2 - 10.1109/TMI.2003.819929
DO - 10.1109/TMI.2003.819929
M3 - Journal article
C2 - 14719685
AN - SCOPUS:0346076622
VL - 23
SP - 36
EP - 44
JO - I E E E Transactions on Medical Imaging
JF - I E E E Transactions on Medical Imaging
SN - 0278-0062
IS - 1
ER -
ID: 302055827