Normalized Cuts in 3-D for Spinal MRI Segmentation

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

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

Harvard

Carballido-Gamio, J, Belongie, SJ & Majumdar, S 2004, 'Normalized Cuts in 3-D for Spinal MRI Segmentation', IEEE Transactions on Medical Imaging, vol. 23, no. 1, pp. 36-44. https://doi.org/10.1109/TMI.2003.819929

APA

Carballido-Gamio, J., Belongie, S. J., & Majumdar, S. (2004). Normalized Cuts in 3-D for Spinal MRI Segmentation. IEEE Transactions on Medical Imaging, 23(1), 36-44. https://doi.org/10.1109/TMI.2003.819929

Vancouver

Carballido-Gamio J, Belongie SJ, Majumdar S. Normalized Cuts in 3-D for Spinal MRI Segmentation. IEEE Transactions on Medical Imaging. 2004 Jan;23(1):36-44. https://doi.org/10.1109/TMI.2003.819929

Author

Carballido-Gamio, Julio ; Belongie, Serge J. ; Majumdar, Sharmila. / Normalized Cuts in 3-D for Spinal MRI Segmentation. In: IEEE Transactions on Medical Imaging. 2004 ; Vol. 23, No. 1. pp. 36-44.

Bibtex

@article{e18f6a57085d4a778ef3515789b5da5d,
title = "Normalized Cuts in 3-D for Spinal MRI Segmentation",
abstract = "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 Nystr{\"o}m approximation method for applications different than medical imaging. In this paper we discuss the application of NCut with the Nystr{\"o}m 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.",
keywords = "Magnetic resonance imaging (MRI), Normalized cuts (NCut), Nystr{\"o}m approximation method, Segmentation, Spine",
author = "Julio Carballido-Gamio and Belongie, {Serge J.} and Sharmila Majumdar",
note = "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.",
year = "2004",
month = jan,
doi = "10.1109/TMI.2003.819929",
language = "English",
volume = "23",
pages = "36--44",
journal = "I E E E Transactions on Medical Imaging",
issn = "0278-0062",
publisher = "Institute of Electrical and Electronics Engineers",
number = "1",

}

RIS

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