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Adaptive Segmentation of Vertebral Bodies from Sagittal MR Images Based on Local Spatial Information and Gaussian Weighted Chi-Square Distance.

We present a novel method for the automatic segmentation of the vertebral bodies from 2D sagittal magnetic resonance (MR) images of the spine. First, a new affinity matrix is constructed by incorporating neighboring information, which local intensity is considered to depict the image and overcome th...

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Published in:Journal of Digital Imaging Vol. 26; no. 3; pp. 578 - 594
Main Authors: Zheng, Qian, Lu, Zhentai, Feng, Qianjin, Ma, Jianhua, Yang, Wei, Chen, Chao, Chen, Wufan
Format: diagnostic images equations & formulas research tables/charts Journal Article
Published: Springer Nature Jun2013
Online Access:View this record in EBSCOhost
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      dt: Jun2013
      vid: 26
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10278-012-9552-9
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        atl: Adaptive Segmentation of Vertebral Bodies from Sagittal MR Images Based on Local Spatial Information and Gaussian Weighted Chi-Square Distance.
      aug:
        au:
          Zheng, Qian
          Lu, Zhentai
          Feng, Qianjin
          Ma, Jianhua
          Yang, Wei
          Chen, Chao
          Chen, Wufan
        affil: School of Biomedical Engineering, Southern Medical University, Guangzhou 510515 China
      sug:
        subj:
          Magnetic Resonance Imaging
          Image Processing, Computer Assisted Methods
          Spine Radiography
          Algorithms
          Artifacts
          Evaluation Research
          Human
          Funding Source
      ab: We present a novel method for the automatic segmentation of the vertebral bodies from 2D sagittal magnetic resonance (MR) images of the spine. First, a new affinity matrix is constructed by incorporating neighboring information, which local intensity is considered to depict the image and overcome the noise effectively. Second, the Gaussian kernel function is to weight chi-square distance based on the neighboring information, which the vital spatial structure of the image is introduced to improve the accuracy of the segmentation task. Third, an adaptive local scaling parameter is utilized to facilitate the image segmentation and avoid the optimal configuration of controlling parameter manually. The encouraging results on the spinal MR images demonstrate the advantage of the proposed method over other methods in terms of both efficiency and robustness.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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