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A two-stage rule-constrained seedless region growing approach for mandibular body segmentation in MRI

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose Extraction of the mandible from 3D volumetric images is frequently required for surgical planning and evaluation. Image segmentation from MRI is more complex than CT due to lower bony signal-to-noise. An automated method to extract the human mandible body shape from magnetic resonance (MR) images of the head was developed and tested.

Methods Anonymous MR images data sets of the head from 12 subjects were subjected to a two-stage rule-constrained region growing approach to derive the shape of the body of the human mandible. An initial thresholding technique was applied followed by a 3D seedless region growing algorithm to detect a large portion of the trabecular bone (TB) regions of the mandible. This stage is followed with a rule-constrained 2D segmentation of each MR axial slice to merge the remaining portions of the TB regions with lower intensity levels. The two-stage approach was replicated to detect the cortical bone (CB) regions of the mandibular body. The TB and CB regions detected from the preceding steps were merged and subjected to a series of morphological processes for completion of the mandibular body region definition. Comparisons of the accuracy of segmentation between the two-stage approach, conventional region growing method, 3D level set method, and manual segmentation were made with Jaccard index, Dice index, and mean surface distance (MSD).

Results The mean accuracy of the proposed method is \(0.958 \,\pm \, 0.020\) for Jaccard index, \(0.979 \,\pm \, 0.011\) for Dice index, and \(0.204 \,\pm \, 0.127\) mm for MSD. The mean accuracy of CRG is \(0.782 \,\pm \, 0.080\) for Jaccard index, \(0.876 \,\pm \, 0.053\) for Dice index, and \(0.417 \,\pm \, 0.073\) mm for MSD. The mean accuracy of the 3D level set method is \(0.874 \,\pm \, 0.0.051\) for Jaccard index, \(0.645 \pm 0.306\) for Dice index, and \(0.645 \pm 0.306\) mm for MSD. The proposed method shows improvement in accuracy over CRG and 3D level set.

Conclusion Accurate segmentation of the body of the human mandible from MR images is achieved with the proposed two-stage rule-constrained seedless region growing approach. The accuracy achieved with the two-stage approach is higher than CRG and 3D level set.

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Acknowledgments

This study is supported by a grant from the Singapore Bio-Imaging Consortium SBIC RP C-007/2006.

Conflict of interest

There is no conflict of interest in this study.

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Authors and Affiliations

  1. NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, Singapore

    Dong Xu Ji, Kelvin Weng Chiong Foong & Sim Heng Ong

  2. Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore

    Dong Xu Ji & Sim Heng Ong

  3. Faculty of Dentistry, National University of Singapore, Singapore, Singapore

    Dong Xu Ji & Kelvin Weng Chiong Foong

  4. Department of Bioengineering, National University of Singapore, Singapore, Singapore

    Sim Heng Ong

Authors
  1. Dong Xu Ji
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  2. Kelvin Weng Chiong Foong
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  3. Sim Heng Ong
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Correspondence to Kelvin Weng Chiong Foong.

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Ji, D.X., Foong, K.W.C. & Ong, S.H. A two-stage rule-constrained seedless region growing approach for mandibular body segmentation in MRI. Int J CARS 8, 723–732 (2013). https://doi.org/10.1007/s11548-012-0806-2

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  • DOI: https://doi.org/10.1007/s11548-012-0806-2

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