Literature DB >> 14719685

Normalized cuts in 3-D for spinal MRI segmentation.

Julio Carballido-Gamio1, Serge J Belongie, Sharmila Majumdar.   

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 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.

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Year:  2004        PMID: 14719685     DOI: 10.1109/TMI.2003.819929

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  18 in total

1.  A 3D active model framework for segmentation of proximal femur in MR images.

Authors:  Sadaf Arezoomand; Won-Sook Lee; Kawan S Rakhra; Paul E Beaulé
Journal:  Int J Comput Assist Radiol Surg       Date:  2014-11-05       Impact factor: 2.924

2.  Adaptive segmentation of vertebral bodies from sagittal MR images based on local spatial information and Gaussian weighted chi-square distance.

Authors:  Qian Zheng; Zhentai Lu; Qianjin Feng; Jianhua Ma; Wei Yang; Chao Chen; Wufan Chen
Journal:  J Digit Imaging       Date:  2013-06       Impact factor: 4.056

Review 3.  On computerized methods for spine analysis in MRI: a systematic review.

Authors:  Marko Rak; Klaus D Tönnies
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-02-09       Impact factor: 2.924

4.  A multi-resolution approach for spinal metastasis detection using deep Siamese neural networks.

Authors:  Juan Wang; Zhiyuan Fang; Ning Lang; Huishu Yuan; Min-Ying Su; Pierre Baldi
Journal:  Comput Biol Med       Date:  2017-03-27       Impact factor: 4.589

5.  Automatic graph-cut based segmentation of bones from knee magnetic resonance images for osteoarthritis research.

Authors:  Sufyan Y Ababneh; Jeff W Prescott; Metin N Gurcan
Journal:  Med Image Anal       Date:  2011-02-24       Impact factor: 8.545

6.  Segmentation of ultrasonic breast tumors based on homogeneous patch.

Authors:  Liang Gao; Wei Yang; Zhiwu Liao; Xiaoyun Liu; Qianjin Feng; Wufan Chen
Journal:  Med Phys       Date:  2012-06       Impact factor: 4.071

7.  Groupwise multi-atlas segmentation of the spinal cord's internal structure.

Authors:  Andrew J Asman; Frederick W Bryan; Seth A Smith; Daniel S Reich; Bennett A Landman
Journal:  Med Image Anal       Date:  2014-02-05       Impact factor: 8.545

8.  A multichannel Markov random field framework for tumor segmentation with an application to classification of gene expression-based breast cancer recurrence risk.

Authors:  Ahmed B Ashraf; Sara C Gavenonis; Dania Daye; Carolyn Mies; Mark A Rosen; Despina Kontos
Journal:  IEEE Trans Med Imaging       Date:  2012-09-19       Impact factor: 10.048

9.  Cube-cut: vertebral body segmentation in MRI-data through cubic-shaped divergences.

Authors:  Robert Schwarzenberg; Bernd Freisleben; Christopher Nimsky; Jan Egger
Journal:  PLoS One       Date:  2014-04-04       Impact factor: 3.240

10.  Quantitative evaluation of an automatic segmentation method for 3D reconstruction of intervertebral scoliotic disks from MR images.

Authors:  Chevrefils Claudia; Cheriet Farida; Grimard Guy; Miron Marie-Claude; Aubin Carl-Eric
Journal:  BMC Med Imaging       Date:  2012-08-02       Impact factor: 1.930

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